CDRIME-MTIS: An enhanced rime optimization-driven multi-threshold segmentation for COVID-19 X-ray images
To improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-adaptive hunting and dispersed foraging strategies, called...
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| Published in | Computers in biology and medicine Vol. 169; p. 107838 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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United States
Elsevier Ltd
01.02.2024
Elsevier Limited |
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| Online Access | Get full text |
| ISSN | 0010-4825 1879-0534 1879-0534 |
| DOI | 10.1016/j.compbiomed.2023.107838 |
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| Abstract | To improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-adaptive hunting and dispersed foraging strategies, called CDRIME. Specifically, the Co-adaptive hunting strategy works in coordination with the basic search rules of RIME at the individual level, which not only facilitates the algorithm to explore the global optimal solution but also enriches the population diversity to a certain extent. The dispersed foraging strategy further enriches the population diversity to help the algorithm break the limitation of local search and thus obtain better convergence. Then, on this basis, a new multi-threshold image segmentation method is proposed by combining the 2D non-local histogram with 2D Kapur entropy, called CDRIME-MTIS. Finally, the results of experiments based on IEEE CEC2017, IEEE CEC2019, and IEEE CEC2022 demonstrate that CDRIME has superior performance than some other basic, advanced, and state-of-the-art algorithms in terms of global search, convergence performance, and escape from local optimality. Meanwhile, the segmentation experiments on COVID-19 X-ray images demonstrate that CDRIME is more advantageous than RIME and other peers in terms of segmentation effect and adaptability to different threshold levels. In conclusion, the proposed CDRIME significantly enhances the global optimization performance and image segmentation of RIME and has great potential to improve COVID-19 diagnosis.
•An improved Rime optimization algorithm is proposed, called CDRIME.•A CDRIME-driven multi-threshold segmentation method is proposed, called CDRIME-MTIS.•CDRIME has excellent exploration, exploitation, and convergence capabilities on IEEE CEC2017.•CDRIME-MTIS is proven to have great potential for improving the diagnosis of COVID-19.•CDRIME successfully optimizes the search defects and segmentation capabilities of RIME. |
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| AbstractList | To improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-adaptive hunting and dispersed foraging strategies, called CDRIME. Specifically, the Co-adaptive hunting strategy works in coordination with the basic search rules of RIME at the individual level, which not only facilitates the algorithm to explore the global optimal solution but also enriches the population diversity to a certain extent. The dispersed foraging strategy further enriches the population diversity to help the algorithm break the limitation of local search and thus obtain better convergence. Then, on this basis, a new multi-threshold image segmentation method is proposed by combining the 2D non-local histogram with 2D Kapur entropy, called CDRIME-MTIS. Finally, the results of experiments based on IEEE CEC2017, IEEE CEC2019, and IEEE CEC2022 demonstrate that CDRIME has superior performance than some other basic, advanced, and state-of-the-art algorithms in terms of global search, convergence performance, and escape from local optimality. Meanwhile, the segmentation experiments on COVID-19 X-ray images demonstrate that CDRIME is more advantageous than RIME and other peers in terms of segmentation effect and adaptability to different threshold levels. In conclusion, the proposed CDRIME significantly enhances the global optimization performance and image segmentation of RIME and has great potential to improve COVID-19 diagnosis.
•An improved Rime optimization algorithm is proposed, called CDRIME.•A CDRIME-driven multi-threshold segmentation method is proposed, called CDRIME-MTIS.•CDRIME has excellent exploration, exploitation, and convergence capabilities on IEEE CEC2017.•CDRIME-MTIS is proven to have great potential for improving the diagnosis of COVID-19.•CDRIME successfully optimizes the search defects and segmentation capabilities of RIME. AbstractTo improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-adaptive hunting and dispersed foraging strategies, called CDRIME. Specifically, the Co-adaptive hunting strategy works in coordination with the basic search rules of RIME at the individual level, which not only facilitates the algorithm to explore the global optimal solution but also enriches the population diversity to a certain extent. The dispersed foraging strategy further enriches the population diversity to help the algorithm break the limitation of local search and thus obtain better convergence. Then, on this basis, a new multi-threshold image segmentation method is proposed by combining the 2D non-local histogram with 2D Kapur entropy, called CDRIME-MTIS. Finally, the results of experiments based on IEEE CEC2017, IEEE CEC2019, and IEEE CEC2022 demonstrate that CDRIME has superior performance than some other basic, advanced, and state-of-the-art algorithms in terms of global search, convergence performance, and escape from local optimality. Meanwhile, the segmentation experiments on COVID-19 X-ray images demonstrate that CDRIME is more advantageous than RIME and other peers in terms of segmentation effect and adaptability to different threshold levels. In conclusion, the proposed CDRIME significantly enhances the global optimization performance and image segmentation of RIME and has great potential to improve COVID-19 diagnosis. To improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-adaptive hunting and dispersed foraging strategies, called CDRIME. Specifically, the Co-adaptive hunting strategy works in coordination with the basic search rules of RIME at the individual level, which not only facilitates the algorithm to explore the global optimal solution but also enriches the population diversity to a certain extent. The dispersed foraging strategy further enriches the population diversity to help the algorithm break the limitation of local search and thus obtain better convergence. Then, on this basis, a new multi-threshold image segmentation method is proposed by combining the 2D non-local histogram with 2D Kapur entropy, called CDRIME-MTIS. Finally, the results of experiments based on IEEE CEC2017, IEEE CEC2019, and IEEE CEC2022 demonstrate that CDRIME has superior performance than some other basic, advanced, and state-of-the-art algorithms in terms of global search, convergence performance, and escape from local optimality. Meanwhile, the segmentation experiments on COVID-19 X-ray images demonstrate that CDRIME is more advantageous than RIME and other peers in terms of segmentation effect and adaptability to different threshold levels. In conclusion, the proposed CDRIME significantly enhances the global optimization performance and image segmentation of RIME and has great potential to improve COVID-19 diagnosis. To improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-adaptive hunting and dispersed foraging strategies, called CDRIME. Specifically, the Co-adaptive hunting strategy works in coordination with the basic search rules of RIME at the individual level, which not only facilitates the algorithm to explore the global optimal solution but also enriches the population diversity to a certain extent. The dispersed foraging strategy further enriches the population diversity to help the algorithm break the limitation of local search and thus obtain better convergence. Then, on this basis, a new multi-threshold image segmentation method is proposed by combining the 2D non-local histogram with 2D Kapur entropy, called CDRIME-MTIS. Finally, the results of experiments based on IEEE CEC2017, IEEE CEC2019, and IEEE CEC2022 demonstrate that CDRIME has superior performance than some other basic, advanced, and state-of-the-art algorithms in terms of global search, convergence performance, and escape from local optimality. Meanwhile, the segmentation experiments on COVID-19 X-ray images demonstrate that CDRIME is more advantageous than RIME and other peers in terms of segmentation effect and adaptability to different threshold levels. In conclusion, the proposed CDRIME significantly enhances the global optimization performance and image segmentation of RIME and has great potential to improve COVID-19 diagnosis.To improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-adaptive hunting and dispersed foraging strategies, called CDRIME. Specifically, the Co-adaptive hunting strategy works in coordination with the basic search rules of RIME at the individual level, which not only facilitates the algorithm to explore the global optimal solution but also enriches the population diversity to a certain extent. The dispersed foraging strategy further enriches the population diversity to help the algorithm break the limitation of local search and thus obtain better convergence. Then, on this basis, a new multi-threshold image segmentation method is proposed by combining the 2D non-local histogram with 2D Kapur entropy, called CDRIME-MTIS. Finally, the results of experiments based on IEEE CEC2017, IEEE CEC2019, and IEEE CEC2022 demonstrate that CDRIME has superior performance than some other basic, advanced, and state-of-the-art algorithms in terms of global search, convergence performance, and escape from local optimality. Meanwhile, the segmentation experiments on COVID-19 X-ray images demonstrate that CDRIME is more advantageous than RIME and other peers in terms of segmentation effect and adaptability to different threshold levels. In conclusion, the proposed CDRIME significantly enhances the global optimization performance and image segmentation of RIME and has great potential to improve COVID-19 diagnosis. |
| ArticleNumber | 107838 |
| Author | Aljehane, Nojood O. Zhao, Dong Escorcia-Gutierrez, José Ma, Chao Li, Yupeng Ye, Xia |
| Author_xml | – sequence: 1 givenname: Yupeng surname: Li fullname: Li, Yupeng email: liyupeng981202@163.com organization: College of Computer Science and Technology, Changchun Normal University, Changchun, Jilin, 130032, China – sequence: 2 givenname: Dong surname: Zhao fullname: Zhao, Dong email: zd-hy@163.com organization: College of Computer Science and Technology, Changchun Normal University, Changchun, Jilin, 130032, China – sequence: 3 givenname: Chao surname: Ma fullname: Ma, Chao email: mac@sziit.edu.cn organization: School of Digital Media, Shenzhen Institute of Information Technology, Shenzhen, 518172, China – sequence: 4 givenname: José orcidid: 0000-0003-0518-3187 surname: Escorcia-Gutierrez fullname: Escorcia-Gutierrez, José email: jescorci56@cuc.edu.co organization: Department of Computational Science and Electronics, Universidad de la Costa, CUC, Barranquilla, 080002, Colombia – sequence: 5 givenname: Nojood O. surname: Aljehane fullname: Aljehane, Nojood O. email: noaljohani@ut.edu.sa organization: Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Kingdom of Saudi Arabia – sequence: 6 givenname: Xia surname: Ye fullname: Ye, Xia email: yex@wmu.edu.cn organization: School of the 1st Clinical Medical Sciences (School of Information and Engineering), Wenzhou Medical University, Wenzhou, 325000, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38171259$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.3390/math9060664 10.1109/ACCESS.2020.3005510 10.1016/j.compbiomed.2021.104941 10.1016/j.knosys.2021.107761 10.1016/j.knosys.2021.107653 10.1109/TIP.2003.819861 10.1016/j.swevo.2011.02.002 10.1109/TSMCB.2012.2222373 10.1109/TIP.2011.2109730 10.1007/s42235-022-00292-z 10.1016/j.knosys.2015.12.022 10.1049/el:20080522 10.1016/j.ins.2014.11.042 10.1016/j.engappai.2018.03.001 10.1016/j.ins.2009.12.010 10.1016/j.compbiomed.2022.105910 10.1016/j.asoc.2021.108291 10.1016/j.asoc.2018.11.047 10.1093/jcde/qwac014 10.1016/j.advengsoft.2017.07.002 10.1016/j.bspc.2023.105147 10.1109/TEVC.2011.2173577 10.1007/s10489-018-1334-8 10.1002/int.22744 10.3389/fbioe.2020.00897 10.1016/j.compbiomed.2022.105510 10.1007/s00500-016-2307-7 10.1007/s00521-015-1870-7 10.3389/fninf.2022.1063048 10.1007/s42235-021-00114-8 10.1016/j.eswa.2022.119041 10.1109/ACCESS.2020.2978102 10.1016/j.energy.2015.12.096 10.1016/j.future.2020.03.055 10.1016/j.compbiomed.2021.105179 10.1016/j.jad.2020.08.017 10.1016/j.advengsoft.2013.12.007 10.1016/j.bspc.2023.104592 10.3390/bioengineering10050529 10.1016/j.asoc.2017.09.039 10.1016/j.compbiomed.2021.104698 10.1109/ACCESS.2020.2973763 10.1007/s42235-022-00297-8 10.1016/j.knosys.2021.107348 10.1016/j.enconman.2021.114223 10.1016/j.compbiomed.2022.105563 10.1016/j.ins.2019.04.022 10.1007/s42235-022-00295-w 10.1109/TETCI.2022.3189054 10.1016/j.knosys.2020.106425 10.1016/j.eswa.2019.07.031 10.1016/j.asoc.2021.108016 10.1016/j.inffus.2021.04.008 10.1016/j.advengsoft.2016.01.008 10.1016/j.future.2019.02.028 10.1007/s42235-022-00228-7 10.1007/s42235-021-0068-1 10.1016/j.eswa.2020.114529 10.1007/s00500-023-08135-7 10.1016/j.neucom.2023.02.010 10.3233/JIFS-152381 10.1007/s42235-022-00304-y 10.3389/fonc.2021.763527 10.1016/j.eswa.2022.118872 10.1016/j.ejor.2006.06.046 10.1016/j.asoc.2019.105499 10.3389/fninf.2023.1126783 10.1016/j.compbiomed.2022.105810 10.1016/j.knosys.2015.07.006 |
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| Keywords | COVID-19 Benchmark Image segmentation RIME Medical diagnosis Population-based method |
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| References | Zhao (bib60) 2020 Hao (bib12) 2023 Wu, Mallipeddi, Suganthan (bib14) 2016 Shan (bib63) 2022; 146 Li (bib31) 2020; 111 He (bib93) 2020; 8 Kumar (bib16) 2022 Hu (bib10) 2020; 8 Price (bib15) 2018 Song (bib41) 2021; 215 Tubishat (bib90) 2019; 49 Hu (bib64) 2021 Lin (bib51) 2023; 20 García (bib17) 2010; 180 Chen (bib89) 2017; 21 Ren (bib91) 2022; 148 Qi (bib71) 2022; 148 Su (bib11) 2022 Houssein (bib27) 2021; 229 Wolpert, Macready (bib44) 1997; 1 Xia (bib49) 2022; 19 Cohen (bib87) 2020 Xu (bib40) 2019; 492 Yu (bib80) 2022 Nenavath, Jatoth (bib39) 2018; 62 Liang (bib82) 2019 Su (bib13) 2023; 532 Tang (bib28) 2020; 8 Mirjalili (bib37) 2016; 96 Storn, Price (bib33) 1997; 11 Hu (bib83) 2023; 20 Lin (bib4) 2023 Maguolo, Nanni (bib8) 2021; 76 Xing (bib26) 2023; 82 Li (bib2) 2020; 277 Liang (bib86) 2021; 113 Mirjalili, Mirjalili, Hatamlou (bib46) 2016; 27 Motta (bib5) 2023; 10 Mittal, Saraswat (bib59) 2018; 71 Xia (bib50) 2021; 18 Li (bib74) 2023; 16 Zhang (bib22) 2021; 139 Han (bib58) 2023; 20 Cai (bib69) 2019; 138 Zhou (bib78) 2021; 230 Mirjalili (bib47) 2017; 114 Tang (bib45) 2019; 81 Zhou (bib21) 2004; 13 Buades, Coll, Morel (bib56) 2005 Xing (bib57) 2023; 20 Adarsh (bib70) 2016; 96 Eddaly (bib79) 2016; 3 Su (bib25) 2022 Chen (bib38) 2022; 142 Qiao (bib85) 2022; 235 Heidari (bib35) 2019; 97 Ahmadianfar (bib67) 2021 Simos (bib1) 2021; 9 Gao (bib6) 2022 Das (bib24) 2023; 27 Qi (bib43) 2022; 9 Ewees, Ismail, Sahlol (bib62) 2023; 213 Yang (bib76) 2022; 145 Ye (bib9) 2022; 116 Hu (bib53) 2022; 237 Liu (bib29) 2020; 8 Zhang (bib19) 2011; 20 Zhang (bib84) 2022 Zhao (bib23) 2023; 17 Zhao (bib68) 2020; 216 Yang (bib77) 2023; 213 Li (bib7) 2023; 7 Hu (bib73) 2022; 37 Yang (bib88) 2010 Kennedy, Eberhart (bib32) 1995 Shi (bib61) 2021; 136 Hu (bib81) 2017; 32 Socha, Dorigo (bib65) 2008; 185 Shan (bib48) 2022; 19 Mirjalili, Mirjalili, Lewis (bib66) 2014; 69 Derrac (bib18) 2011; 1 Gao, Liu, Huang (bib54) 2013; 43 Xie (bib3) 2021; 11 Li, Yin (bib55) 2015; 298 Mirjalili (bib30) 2015; 89 Weng (bib75) 2021; 243 Li (bib72) 2021; 171 Chen (bib42) 2013; 17 Tu, Chen, Liu (bib52) 2019; 76 Huynh-Thu, Ghanbari (bib20) 2008; 44 Mirjalili, Lewis (bib34) 2016; 95 Karaboga (bib36) 2005 Sun (bib92) 2023 Su (10.1016/j.compbiomed.2023.107838_bib13) 2023; 532 Tubishat (10.1016/j.compbiomed.2023.107838_bib90) 2019; 49 Zhou (10.1016/j.compbiomed.2023.107838_bib21) 2004; 13 Zhao (10.1016/j.compbiomed.2023.107838_bib23) 2023; 17 Hu (10.1016/j.compbiomed.2023.107838_bib73) 2022; 37 Ewees (10.1016/j.compbiomed.2023.107838_bib62) 2023; 213 Wu (10.1016/j.compbiomed.2023.107838_bib14) 2016 Derrac (10.1016/j.compbiomed.2023.107838_bib18) 2011; 1 Sun (10.1016/j.compbiomed.2023.107838_bib92) 2023 Hu (10.1016/j.compbiomed.2023.107838_bib10) 2020; 8 Gao (10.1016/j.compbiomed.2023.107838_bib54) 2013; 43 Buades (10.1016/j.compbiomed.2023.107838_bib56) 2005 Simos (10.1016/j.compbiomed.2023.107838_bib1) 2021; 9 Lin (10.1016/j.compbiomed.2023.107838_bib51) 2023; 20 Gao (10.1016/j.compbiomed.2023.107838_bib6) 2022 Price (10.1016/j.compbiomed.2023.107838_bib15) 2018 He (10.1016/j.compbiomed.2023.107838_bib93) 2020; 8 Houssein (10.1016/j.compbiomed.2023.107838_bib27) 2021; 229 Ye (10.1016/j.compbiomed.2023.107838_bib9) 2022; 116 Li (10.1016/j.compbiomed.2023.107838_bib55) 2015; 298 Xing (10.1016/j.compbiomed.2023.107838_bib57) 2023; 20 Zhao (10.1016/j.compbiomed.2023.107838_bib68) 2020; 216 Qi (10.1016/j.compbiomed.2023.107838_bib71) 2022; 148 Karaboga (10.1016/j.compbiomed.2023.107838_bib36) 2005 Huynh-Thu (10.1016/j.compbiomed.2023.107838_bib20) 2008; 44 Tang (10.1016/j.compbiomed.2023.107838_bib28) 2020; 8 Liang (10.1016/j.compbiomed.2023.107838_bib86) 2021; 113 Shan (10.1016/j.compbiomed.2023.107838_bib48) 2022; 19 Li (10.1016/j.compbiomed.2023.107838_bib31) 2020; 111 Mirjalili (10.1016/j.compbiomed.2023.107838_bib37) 2016; 96 Kennedy (10.1016/j.compbiomed.2023.107838_bib32) 1995 Yang (10.1016/j.compbiomed.2023.107838_bib88) 2010 Li (10.1016/j.compbiomed.2023.107838_bib74) 2023; 16 Li (10.1016/j.compbiomed.2023.107838_bib7) 2023; 7 Mirjalili (10.1016/j.compbiomed.2023.107838_bib30) 2015; 89 Zhang (10.1016/j.compbiomed.2023.107838_bib84) 2022 Hao (10.1016/j.compbiomed.2023.107838_bib12) 2023 Wolpert (10.1016/j.compbiomed.2023.107838_bib44) 1997; 1 Li (10.1016/j.compbiomed.2023.107838_bib72) 2021; 171 Yu (10.1016/j.compbiomed.2023.107838_bib80) 2022 Weng (10.1016/j.compbiomed.2023.107838_bib75) 2021; 243 Xia (10.1016/j.compbiomed.2023.107838_bib49) 2022; 19 Hu (10.1016/j.compbiomed.2023.107838_bib81) 2017; 32 Mittal (10.1016/j.compbiomed.2023.107838_bib59) 2018; 71 Mirjalili (10.1016/j.compbiomed.2023.107838_bib47) 2017; 114 Shi (10.1016/j.compbiomed.2023.107838_bib61) 2021; 136 Lin (10.1016/j.compbiomed.2023.107838_bib4) 2023 Heidari (10.1016/j.compbiomed.2023.107838_bib35) 2019; 97 Su (10.1016/j.compbiomed.2023.107838_bib11) 2022 Adarsh (10.1016/j.compbiomed.2023.107838_bib70) 2016; 96 Storn (10.1016/j.compbiomed.2023.107838_bib33) 1997; 11 Socha (10.1016/j.compbiomed.2023.107838_bib65) 2008; 185 Chen (10.1016/j.compbiomed.2023.107838_bib89) 2017; 21 Tang (10.1016/j.compbiomed.2023.107838_bib45) 2019; 81 Han (10.1016/j.compbiomed.2023.107838_bib58) 2023; 20 Tu (10.1016/j.compbiomed.2023.107838_bib52) 2019; 76 Chen (10.1016/j.compbiomed.2023.107838_bib38) 2022; 142 Yang (10.1016/j.compbiomed.2023.107838_bib77) 2023; 213 Cohen (10.1016/j.compbiomed.2023.107838_bib87) 2020 Zhang (10.1016/j.compbiomed.2023.107838_bib22) 2021; 139 Xia (10.1016/j.compbiomed.2023.107838_bib50) 2021; 18 Xie (10.1016/j.compbiomed.2023.107838_bib3) 2021; 11 Liu (10.1016/j.compbiomed.2023.107838_bib29) 2020; 8 Ren (10.1016/j.compbiomed.2023.107838_bib91) 2022; 148 Hu (10.1016/j.compbiomed.2023.107838_bib53) 2022; 237 Yang (10.1016/j.compbiomed.2023.107838_bib76) 2022; 145 Qi (10.1016/j.compbiomed.2023.107838_bib43) 2022; 9 Cai (10.1016/j.compbiomed.2023.107838_bib69) 2019; 138 Motta (10.1016/j.compbiomed.2023.107838_bib5) 2023; 10 Zhang (10.1016/j.compbiomed.2023.107838_bib19) 2011; 20 Li (10.1016/j.compbiomed.2023.107838_bib2) 2020; 277 Maguolo (10.1016/j.compbiomed.2023.107838_bib8) 2021; 76 Ahmadianfar (10.1016/j.compbiomed.2023.107838_bib67) 2021 Mirjalili (10.1016/j.compbiomed.2023.107838_bib66) 2014; 69 Liang (10.1016/j.compbiomed.2023.107838_bib82) 2019 Mirjalili (10.1016/j.compbiomed.2023.107838_bib34) 2016; 95 Hu (10.1016/j.compbiomed.2023.107838_bib64) 2021 Chen (10.1016/j.compbiomed.2023.107838_bib42) 2013; 17 Mirjalili (10.1016/j.compbiomed.2023.107838_bib46) 2016; 27 Qiao (10.1016/j.compbiomed.2023.107838_bib85) 2022; 235 Zhao (10.1016/j.compbiomed.2023.107838_bib60) 2020 Kumar (10.1016/j.compbiomed.2023.107838_bib16) 2022 Das (10.1016/j.compbiomed.2023.107838_bib24) 2023; 27 Nenavath (10.1016/j.compbiomed.2023.107838_bib39) 2018; 62 Xing (10.1016/j.compbiomed.2023.107838_bib26) 2023; 82 Su (10.1016/j.compbiomed.2023.107838_bib25) 2022 Song (10.1016/j.compbiomed.2023.107838_bib41) 2021; 215 Shan (10.1016/j.compbiomed.2023.107838_bib63) 2022; 146 Zhou (10.1016/j.compbiomed.2023.107838_bib78) 2021; 230 García (10.1016/j.compbiomed.2023.107838_bib17) 2010; 180 Eddaly (10.1016/j.compbiomed.2023.107838_bib79) 2016; 3 Xu (10.1016/j.compbiomed.2023.107838_bib40) 2019; 492 Hu (10.1016/j.compbiomed.2023.107838_bib83) 2023; 20 |
| References_xml | – year: 2018 ident: bib15 article-title: Problem definitions and evaluation criteria for the 100-digit challenge special session and competition on single objective numerical optimization publication-title: Technical Report – volume: 1 start-page: 67 year: 1997 end-page: 82 ident: bib44 article-title: No free lunch theorems for optimization – volume: 27 start-page: 18991 year: 2023 end-page: 19011 ident: bib24 article-title: A non-entropy-based optimal multilevel threshold selection technique for COVID-19 X-ray images using chance-based birds' intelligence publication-title: Soft Comput. – volume: 20 start-page: 1296 year: 2023 end-page: 1332 ident: bib51 article-title: A boosted communicational salp swarm algorithm: performance optimization and comprehensive analysis publication-title: Journal of Bionic Engineering – volume: 171 year: 2021 ident: bib72 article-title: Memetic Harris Hawks Optimization: developments and perspectives on project scheduling and QoS-aware web service composition publication-title: Expert Syst. Appl. – year: 2022 ident: bib80 article-title: Apple Leaf Disease Recognition Method with Improved Residual Network – volume: 11 year: 2021 ident: bib3 article-title: Evaluating cancer-related biomarkers based on pathological images: a systematic review publication-title: Front. Oncol. – volume: 89 start-page: 228 year: 2015 end-page: 249 ident: bib30 article-title: Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm publication-title: Knowl. Base Syst. – volume: 62 start-page: 1019 year: 2018 end-page: 1043 ident: bib39 article-title: Hybridizing sine cosine algorithm with differential evolution for global optimization and object tracking publication-title: Appl. Soft Comput. – volume: 298 start-page: 80 year: 2015 end-page: 97 ident: bib55 article-title: Modified cuckoo search algorithm with self adaptive parameter method publication-title: Inf. Sci. – year: 2020 ident: bib60 article-title: Chaotic Random Spare Ant Colony Optimization for Multi-Threshold Image Segmentation of 2D Kapur Entropy – volume: 277 start-page: 153 year: 2020 end-page: 158 ident: bib2 article-title: Prevalence and factors for anxiety during the coronavirus disease 2019 (COVID-19) epidemic among the teachers in China publication-title: J. Affect. Disord. – volume: 111 start-page: 300 year: 2020 end-page: 323 ident: bib31 article-title: Slime mould algorithm: a new method for stochastic optimization publication-title: Future Generat. Comput. Syst. – volume: 19 start-page: 240 year: 2022 end-page: 256 ident: bib49 article-title: Adaptive barebones salp swarm algorithm with quasi-oppositional learning for medical diagnosis systems: a comprehensive analysis publication-title: Journal of Bionic Engineering – volume: 213 year: 2023 ident: bib62 article-title: Gradient-based optimizer improved by Slime Mould Algorithm for global optimization and feature selection for diverse computation problems publication-title: Expert Syst. Appl. – year: 1995 ident: bib32 article-title: Particle swarm optimization publication-title: Proceedings of ICNN'95 - International Conference on Neural Networks – volume: 148 year: 2022 ident: bib91 article-title: Multi-level thresholding segmentation for pathological images: optimal performance design of a new modified differential evolution publication-title: Comput. Biol. Med. – volume: 185 start-page: 1155 year: 2008 end-page: 1173 ident: bib65 article-title: Ant colony optimization for continuous domains publication-title: Eur. J. Oper. Res. – volume: 8 start-page: 118869 year: 2020 end-page: 118883 ident: bib10 article-title: Weakly supervised deep learning for COVID-19 infection detection and classification from CT images publication-title: IEEE Access – start-page: 65 year: 2010 end-page: 74 ident: bib88 article-title: A new metaheuristic bat-inspired algorithm publication-title: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) – year: 2005 ident: bib36 article-title: An Idea Based on Honey Bee Swarm for Numerical Optimization – volume: 492 start-page: 181 year: 2019 end-page: 203 ident: bib40 article-title: Enhanced Moth-flame optimizer with mutation strategy for global optimization publication-title: Inf. Sci. – volume: 69 start-page: 46 year: 2014 end-page: 61 ident: bib66 article-title: Grey wolf optimizer publication-title: Adv. Eng. Software – year: 2023 ident: bib4 article-title: A novel approach of surface texture mapping for cone-beam computed tomography in image-guided surgical navigation publication-title: IEEE J. Biomed. Health Inform. – year: 2023 ident: bib12 article-title: Multi-threshold image segmentation using an enhanced fruit fly optimization for COVID-19 X-ray images publication-title: Biomed. Signal Process Control – volume: 11 start-page: 341 year: 1997 end-page: 359 ident: bib33 article-title: Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces – year: 2016 ident: bib14 article-title: Problem Definitions and Evaluation Criteria for the CEC 2017 Competition and Special Session on Constrained Single Objective Real-Parameter Optimization – volume: 37 start-page: 4864 year: 2022 end-page: 4927 ident: bib73 article-title: Chaotic diffusion‐limited aggregation enhanced grey wolf optimizer: insights, analysis, binarization, and feature selection publication-title: Int. J. Intell. Syst. – year: 2023 ident: bib92 article-title: Few-shot class-incremental learning for medical time series classification publication-title: IEEE J. Biomed. Health Inform. – volume: 43 start-page: 1011 year: 2013 end-page: 1024 ident: bib54 article-title: A novel artificial bee colony algorithm based on modified search equation and orthogonal learning publication-title: IEEE Trans. Cybern. – volume: 235 year: 2022 ident: bib85 article-title: Self-adaptive resources allocation-based differential evolution for constrained evolutionary optimization publication-title: Knowl. Base Syst. – volume: 20 start-page: 2378 year: 2011 end-page: 2386 ident: bib19 article-title: FSIM: a feature similarity index for image quality assessment publication-title: IEEE Trans. Image Process. – volume: 20 start-page: 797 year: 2023 end-page: 818 ident: bib57 article-title: Boosting whale optimizer with quasi-oppositional learning and Gaussian barebone for feature selection and COVID-19 image segmentation publication-title: Journal of Bionic Engineering – volume: 19 start-page: 1830 year: 2022 end-page: 1849 ident: bib48 article-title: Multi-strategies boosted mutative crow search algorithm for global tasks: cases of continuous and discrete optimization publication-title: Journal of Bionic Engineering – volume: 116 year: 2022 ident: bib9 article-title: Robust weakly supervised learning for COVID-19 recognition using multi-center CT images publication-title: Appl. Soft Comput. – volume: 213 year: 2023 ident: bib77 article-title: An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems publication-title: Expert Syst. Appl. – volume: 44 start-page: 800 year: 2008 end-page: 801 ident: bib20 article-title: Scope of validity of PSNR in image/video quality assessment publication-title: Electron. Lett. – volume: 138 year: 2019 ident: bib69 article-title: Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy publication-title: Expert Syst. Appl. – volume: 8 start-page: 897 year: 2020 ident: bib93 article-title: A new method for CTC images recognition based on machine learning publication-title: Front. Bioeng. Biotechnol. – volume: 1 start-page: 3 year: 2011 end-page: 18 ident: bib18 article-title: A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms publication-title: Swarm Evol. Comput. – volume: 76 start-page: 16 year: 2019 end-page: 30 ident: bib52 article-title: Multi-strategy ensemble grey wolf optimizer and its application to feature selection publication-title: Appl. Soft Comput. – volume: 230 year: 2021 ident: bib78 article-title: Random learning gradient based optimization for efficient design of photovoltaic models (Energy Conversion and Management, Impact Factor: 9.709) publication-title: Energy Convers. Manag. – volume: 7 start-page: 26 year: 2023 end-page: 35 ident: bib7 article-title: Explainable COVID-19 infections identification and delineation using calibrated pseudo labels publication-title: IEEE Trans. Emerg. Topics Comput. Intellig. – volume: 81 year: 2019 ident: bib45 article-title: Spherical evolution for solving continuous optimization problems publication-title: Appl. Soft Comput. – volume: 96 start-page: 666 year: 2016 end-page: 675 ident: bib70 article-title: Economic dispatch using chaotic bat algorithm publication-title: Energy – volume: 32 start-page: 1775 year: 2017 end-page: 1786 ident: bib81 article-title: A novel object tracking algorithm by fusing color and depth information based on single valued neutrosophic cross-entropy publication-title: J. Intell. Fuzzy Syst. – volume: 8 start-page: 46895 year: 2020 end-page: 46908 ident: bib29 article-title: Predicting cervical hyperextension injury: a covariance guided sine cosine support vector machine publication-title: IEEE Access – year: 2021 ident: bib64 article-title: Chaotic diffusion‐limited aggregation enhanced grey wolf optimizer: insights, analysis, binarization, and feature selection (Intelligent Systems, impact factor:8.709) publication-title: Int. J. Intell. Syst. – volume: 10 start-page: 529 year: 2023 ident: bib5 article-title: Automatic COVID-19 and common-acquired pneumonia diagnosis using chest CT scans publication-title: Bioengineering – year: 2022 ident: bib6 article-title: Automatic interpretation and clinical evaluation for fundus fluorescein angiography images of diabetic retinopathy patients by deep learning publication-title: Br. J. Ophthalmol. – volume: 216 year: 2020 ident: bib68 article-title: Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy publication-title: Knowl. Base Syst. – volume: 9 start-page: 519 year: 2022 end-page: 563 ident: bib43 article-title: Directional mutation and crossover for immature performance of whale algorithm with application to engineering optimization publication-title: Journal of Computational Design and Engineering – start-page: 138 year: 2019 ident: bib82 article-title: A hybrid of genetic transform and hyper-rectangle search strategies for evolutionary multi-tasking publication-title: Expert Syst. Appl. – year: 2022 ident: bib84 article-title: Differential evolution-assisted salp swarm algorithm with chaotic structure for real-world problems publication-title: Eng. Comput. – volume: 114 start-page: 163 year: 2017 end-page: 191 ident: bib47 article-title: Salp Swarm Algorithm: a bio-inspired optimizer for engineering design problems publication-title: Adv. Eng. Software – volume: 13 start-page: 600 year: 2004 end-page: 612 ident: bib21 article-title: Image quality assessment: from error visibility to structural similarity publication-title: IEEE Trans. Image Process. – volume: 243 year: 2021 ident: bib75 article-title: Laplacian Nelder-Mead spherical evolution for parameter estimation of photovoltaic models publication-title: Energy Convers. Manag. – volume: 237 year: 2022 ident: bib53 article-title: Dispersed foraging slime mould algorithm: continuous and binary variants for global optimization and wrapper-based feature selection publication-title: Knowl. Base Syst. – volume: 20 start-page: 1198 year: 2023 end-page: 1262 ident: bib58 article-title: Multi-verse optimizer with rosenbrock and diffusion mechanisms for multilevel threshold image segmentation from COVID-19 chest X-ray images publication-title: Journal of Bionic Engineering – volume: 9 start-page: 664 year: 2021 ident: bib1 article-title: Real-time estimation of R0 for COVID-19 spread publication-title: Mathematics – volume: 113 year: 2021 ident: bib86 article-title: Differential evolution with rankings-based fitness function for constrained optimization problems publication-title: Appl. Soft Comput. – volume: 97 start-page: 849 year: 2019 end-page: 872 ident: bib35 article-title: Harris hawks optimization: algorithm and applications publication-title: Future Generat. Comput. Syst. – year: 2021 ident: bib67 article-title: RUN beyond the Metaphor: an Efficient Optimization Algorithm Based on Runge Kutta Method – volume: 148 year: 2022 ident: bib71 article-title: Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation publication-title: Comput. Biol. Med. – volume: 142 year: 2022 ident: bib38 article-title: An efficient multilevel thresholding image segmentation method based on the slime mould algorithm with bee foraging mechanism: a real case with lupus nephritis images publication-title: Comput. Biol. Med. – volume: 21 start-page: 7519 year: 2017 end-page: 7541 ident: bib89 article-title: Biogeography-based learning particle swarm optimization publication-title: Soft Comput. – volume: 3 start-page: 295 year: 2016 end-page: 311 ident: bib79 article-title: Combinatorial particle swarm optimization for solving blocking flowshop scheduling problem – volume: 49 start-page: 1688 year: 2019 end-page: 1707 ident: bib90 article-title: Improved whale optimization algorithm for feature selection in Arabic sentiment analysis publication-title: Appl. Intell. – year: 2005 ident: bib56 article-title: A non-local algorithm for image denoising publication-title: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition – volume: 95 start-page: 51 year: 2016 end-page: 67 ident: bib34 article-title: The whale optimization algorithm publication-title: Adv. Eng. Software – volume: 18 start-page: 991 year: 2021 end-page: 1010 ident: bib50 article-title: Generalized oppositional Moth flame optimization with crossover strategy: an approach for medical diagnosis publication-title: Journal of Bionic Engineering – volume: 16 year: 2023 ident: bib74 article-title: bSRWPSO-FKNN: a boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease publication-title: Front. Neuroinf. – volume: 82 year: 2023 ident: bib26 article-title: Elite levy spreading differential evolution via ABC shrink-wrap for multi-threshold segmentation of breast cancer images publication-title: Biomed. Signal Process Control – volume: 27 start-page: 495 year: 2016 end-page: 513 ident: bib46 article-title: Multi-Verse Optimizer: a nature-inspired algorithm for global optimization publication-title: Neural Comput. Appl. – volume: 8 start-page: 35546 year: 2020 end-page: 35562 ident: bib28 article-title: Predicting green consumption behaviors of students using efficient firefly grey wolf-assisted K-nearest neighbor classifiers publication-title: IEEE Access – volume: 532 start-page: 183 year: 2023 end-page: 214 ident: bib13 article-title: RIME: a physics-based optimization publication-title: Neurocomputing – volume: 17 start-page: 241 year: 2013 end-page: 258 ident: bib42 article-title: Particle swarm optimization with an aging leader and challengers publication-title: IEEE Trans. Evol. Comput. – volume: 215 year: 2021 ident: bib41 article-title: Dimension decided Harris hawks optimization with Gaussian mutation: balance analysis and diversity patterns publication-title: Knowl. Base Syst. – start-page: 146 year: 2022 ident: bib11 article-title: Multilevel threshold image segmentation for COVID-19 chest radiography: a framework using horizontal and vertical multiverse optimization publication-title: Comput. Biol. Med. – year: 2022 ident: bib16 article-title: Problem Definitions and Evaluation Criteria for the CEC 2022 Special Session and Competition on Single Objective Bound Constrained Numerical Optimization – start-page: 142 year: 2022 ident: bib25 article-title: Horizontal and vertical search artificial bee colony for image segmentation of COVID-19 X-ray images publication-title: Comput. Biol. Med. – volume: 71 start-page: 226 year: 2018 end-page: 235 ident: bib59 article-title: An optimum multi-level image thresholding segmentation using non-local means 2D histogram and exponential Kbest gravitational search algorithm publication-title: Eng. Appl. Artif. Intell. – volume: 229 year: 2021 ident: bib27 article-title: An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation publication-title: Knowl. Base Syst. – volume: 136 year: 2021 ident: bib61 article-title: Evolutionary warning system for COVID-19 severity: colony predation algorithm enhanced extreme learning machine publication-title: Comput. Biol. Med. – year: 2020 ident: bib87 article-title: Covid-19 Image Data Collection: Prospective Predictions Are the Future – volume: 180 start-page: 2044 year: 2010 end-page: 2064 ident: bib17 article-title: Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power publication-title: Inf. Sci. – volume: 96 start-page: 120 year: 2016 end-page: 133 ident: bib37 article-title: SCA: a sine cosine algorithm for solving optimization problems publication-title: Knowl. Base Syst. – volume: 76 start-page: 1 year: 2021 end-page: 7 ident: bib8 article-title: A critic evaluation of methods for covid-19 automatic detection from x-ray images publication-title: Inf. Fusion – volume: 17 year: 2023 ident: bib23 article-title: An enhanced ant colony optimizer with Cauchy-Gaussian fusion and novel movement strategy for multi-threshold COVID-19 X-ray image segmentation publication-title: Front. Neuroinf. – volume: 146 year: 2022 ident: bib63 article-title: An efficient rotational direction heap-based optimization with orthogonal structure for medical diagnosis publication-title: Comput. Biol. Med. – volume: 139 year: 2021 ident: bib22 article-title: Gaussian barebone salp swarm algorithm with stochastic fractal search for medical image segmentation: a COVID-19 case study publication-title: Comput. Biol. Med. – volume: 145 year: 2022 ident: bib76 article-title: An optimized machine learning framework for predicting intradialytic hypotension using indexes of chronic kidney disease-mineral and bone disorders publication-title: Comput. Biol. Med. – volume: 20 start-page: 762 year: 2023 end-page: 781 ident: bib83 article-title: Identification of pulmonary hypertension animal models using a new evolutionary machine learning framework based on blood routine indicators publication-title: Journal of Bionic Engineering – volume: 9 start-page: 664 issue: 6 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib1 article-title: Real-time estimation of R0 for COVID-19 spread publication-title: Mathematics doi: 10.3390/math9060664 – volume: 230 issue: 29 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib78 article-title: Random learning gradient based optimization for efficient design of photovoltaic models (Energy Conversion and Management, Impact Factor: 9.709) publication-title: Energy Convers. Manag. – volume: 8 start-page: 118869 year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib10 article-title: Weakly supervised deep learning for COVID-19 infection detection and classification from CT images publication-title: IEEE Access doi: 10.1109/ACCESS.2020.3005510 – start-page: 146 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib11 article-title: Multilevel threshold image segmentation for COVID-19 chest radiography: a framework using horizontal and vertical multiverse optimization publication-title: Comput. Biol. Med. – year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib16 – volume: 139 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib22 article-title: Gaussian barebone salp swarm algorithm with stochastic fractal search for medical image segmentation: a COVID-19 case study publication-title: Comput. Biol. Med. doi: 10.1016/j.compbiomed.2021.104941 – year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib80 – volume: 237 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib53 article-title: Dispersed foraging slime mould algorithm: continuous and binary variants for global optimization and wrapper-based feature selection publication-title: Knowl. Base Syst. doi: 10.1016/j.knosys.2021.107761 – volume: 235 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib85 article-title: Self-adaptive resources allocation-based differential evolution for constrained evolutionary optimization publication-title: Knowl. Base Syst. doi: 10.1016/j.knosys.2021.107653 – volume: 13 start-page: 600 issue: 4 year: 2004 ident: 10.1016/j.compbiomed.2023.107838_bib21 article-title: Image quality assessment: from error visibility to structural similarity publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2003.819861 – volume: 1 start-page: 3 issue: 1 year: 2011 ident: 10.1016/j.compbiomed.2023.107838_bib18 article-title: A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2011.02.002 – volume: 43 start-page: 1011 issue: 3 year: 2013 ident: 10.1016/j.compbiomed.2023.107838_bib54 article-title: A novel artificial bee colony algorithm based on modified search equation and orthogonal learning publication-title: IEEE Trans. Cybern. doi: 10.1109/TSMCB.2012.2222373 – volume: 3 start-page: 295 issue: 4 year: 2016 ident: 10.1016/j.compbiomed.2023.107838_bib79 article-title: Combinatorial particle swarm optimization for solving blocking flowshop scheduling problem – volume: 20 start-page: 2378 issue: 8 year: 2011 ident: 10.1016/j.compbiomed.2023.107838_bib19 article-title: FSIM: a feature similarity index for image quality assessment publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2011.2109730 – volume: 20 start-page: 762 issue: 2 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib83 article-title: Identification of pulmonary hypertension animal models using a new evolutionary machine learning framework based on blood routine indicators publication-title: Journal of Bionic Engineering doi: 10.1007/s42235-022-00292-z – volume: 96 start-page: 120 year: 2016 ident: 10.1016/j.compbiomed.2023.107838_bib37 article-title: SCA: a sine cosine algorithm for solving optimization problems publication-title: Knowl. Base Syst. doi: 10.1016/j.knosys.2015.12.022 – volume: 44 start-page: 800 year: 2008 ident: 10.1016/j.compbiomed.2023.107838_bib20 article-title: Scope of validity of PSNR in image/video quality assessment publication-title: Electron. Lett. doi: 10.1049/el:20080522 – volume: 298 start-page: 80 year: 2015 ident: 10.1016/j.compbiomed.2023.107838_bib55 article-title: Modified cuckoo search algorithm with self adaptive parameter method publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.11.042 – year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib87 – start-page: 142 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib25 article-title: Horizontal and vertical search artificial bee colony for image segmentation of COVID-19 X-ray images publication-title: Comput. Biol. Med. – volume: 71 start-page: 226 year: 2018 ident: 10.1016/j.compbiomed.2023.107838_bib59 article-title: An optimum multi-level image thresholding segmentation using non-local means 2D histogram and exponential Kbest gravitational search algorithm publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2018.03.001 – volume: 180 start-page: 2044 issue: 10 year: 2010 ident: 10.1016/j.compbiomed.2023.107838_bib17 article-title: Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power publication-title: Inf. Sci. doi: 10.1016/j.ins.2009.12.010 – year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib6 article-title: Automatic interpretation and clinical evaluation for fundus fluorescein angiography images of diabetic retinopathy patients by deep learning publication-title: Br. J. Ophthalmol. – year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib67 – volume: 148 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib91 article-title: Multi-level thresholding segmentation for pathological images: optimal performance design of a new modified differential evolution publication-title: Comput. Biol. Med. doi: 10.1016/j.compbiomed.2022.105910 – volume: 116 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib9 article-title: Robust weakly supervised learning for COVID-19 recognition using multi-center CT images publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2021.108291 – volume: 76 start-page: 16 year: 2019 ident: 10.1016/j.compbiomed.2023.107838_bib52 article-title: Multi-strategy ensemble grey wolf optimizer and its application to feature selection publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2018.11.047 – volume: 9 start-page: 519 issue: 2 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib43 article-title: Directional mutation and crossover for immature performance of whale algorithm with application to engineering optimization publication-title: Journal of Computational Design and Engineering doi: 10.1093/jcde/qwac014 – volume: 114 start-page: 163 year: 2017 ident: 10.1016/j.compbiomed.2023.107838_bib47 article-title: Salp Swarm Algorithm: a bio-inspired optimizer for engineering design problems publication-title: Adv. Eng. Software doi: 10.1016/j.advengsoft.2017.07.002 – year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib12 article-title: Multi-threshold image segmentation using an enhanced fruit fly optimization for COVID-19 X-ray images publication-title: Biomed. Signal Process Control doi: 10.1016/j.bspc.2023.105147 – volume: 17 start-page: 241 issue: 2 year: 2013 ident: 10.1016/j.compbiomed.2023.107838_bib42 article-title: Particle swarm optimization with an aging leader and challengers publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2011.2173577 – volume: 49 start-page: 1688 issue: 5 year: 2019 ident: 10.1016/j.compbiomed.2023.107838_bib90 article-title: Improved whale optimization algorithm for feature selection in Arabic sentiment analysis publication-title: Appl. Intell. doi: 10.1007/s10489-018-1334-8 – year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib4 article-title: A novel approach of surface texture mapping for cone-beam computed tomography in image-guided surgical navigation publication-title: IEEE J. Biomed. Health Inform. – year: 2018 ident: 10.1016/j.compbiomed.2023.107838_bib15 article-title: Problem definitions and evaluation criteria for the 100-digit challenge special session and competition on single objective numerical optimization – volume: 37 start-page: 4864 issue: 8 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib73 article-title: Chaotic diffusion‐limited aggregation enhanced grey wolf optimizer: insights, analysis, binarization, and feature selection publication-title: Int. J. Intell. Syst. doi: 10.1002/int.22744 – volume: 8 start-page: 897 year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib93 article-title: A new method for CTC images recognition based on machine learning publication-title: Front. Bioeng. Biotechnol. doi: 10.3389/fbioe.2020.00897 – volume: 145 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib76 article-title: An optimized machine learning framework for predicting intradialytic hypotension using indexes of chronic kidney disease-mineral and bone disorders publication-title: Comput. Biol. Med. doi: 10.1016/j.compbiomed.2022.105510 – volume: 21 start-page: 7519 issue: 24 year: 2017 ident: 10.1016/j.compbiomed.2023.107838_bib89 article-title: Biogeography-based learning particle swarm optimization publication-title: Soft Comput. doi: 10.1007/s00500-016-2307-7 – volume: 27 start-page: 495 issue: 2 year: 2016 ident: 10.1016/j.compbiomed.2023.107838_bib46 article-title: Multi-Verse Optimizer: a nature-inspired algorithm for global optimization publication-title: Neural Comput. Appl. doi: 10.1007/s00521-015-1870-7 – volume: 16 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib74 article-title: bSRWPSO-FKNN: a boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease publication-title: Front. Neuroinf. doi: 10.3389/fninf.2022.1063048 – volume: 19 start-page: 240 issue: 1 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib49 article-title: Adaptive barebones salp swarm algorithm with quasi-oppositional learning for medical diagnosis systems: a comprehensive analysis publication-title: Journal of Bionic Engineering doi: 10.1007/s42235-021-00114-8 – volume: 216 year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib68 article-title: Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy publication-title: Knowl. Base Syst. – volume: 213 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib77 article-title: An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2022.119041 – volume: 8 start-page: 46895 year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib29 article-title: Predicting cervical hyperextension injury: a covariance guided sine cosine support vector machine publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2978102 – volume: 96 start-page: 666 year: 2016 ident: 10.1016/j.compbiomed.2023.107838_bib70 article-title: Economic dispatch using chaotic bat algorithm publication-title: Energy doi: 10.1016/j.energy.2015.12.096 – volume: 111 start-page: 300 year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib31 article-title: Slime mould algorithm: a new method for stochastic optimization publication-title: Future Generat. Comput. Syst. doi: 10.1016/j.future.2020.03.055 – year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib92 article-title: Few-shot class-incremental learning for medical time series classification publication-title: IEEE J. Biomed. Health Inform. – volume: 142 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib38 article-title: An efficient multilevel thresholding image segmentation method based on the slime mould algorithm with bee foraging mechanism: a real case with lupus nephritis images publication-title: Comput. Biol. Med. doi: 10.1016/j.compbiomed.2021.105179 – volume: 277 start-page: 153 year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib2 article-title: Prevalence and factors for anxiety during the coronavirus disease 2019 (COVID-19) epidemic among the teachers in China publication-title: J. Affect. Disord. doi: 10.1016/j.jad.2020.08.017 – year: 1995 ident: 10.1016/j.compbiomed.2023.107838_bib32 article-title: Particle swarm optimization – volume: 69 start-page: 46 year: 2014 ident: 10.1016/j.compbiomed.2023.107838_bib66 article-title: Grey wolf optimizer publication-title: Adv. Eng. Software doi: 10.1016/j.advengsoft.2013.12.007 – volume: 82 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib26 article-title: Elite levy spreading differential evolution via ABC shrink-wrap for multi-threshold segmentation of breast cancer images publication-title: Biomed. Signal Process Control doi: 10.1016/j.bspc.2023.104592 – volume: 10 start-page: 529 issue: 5 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib5 article-title: Automatic COVID-19 and common-acquired pneumonia diagnosis using chest CT scans publication-title: Bioengineering doi: 10.3390/bioengineering10050529 – volume: 62 start-page: 1019 year: 2018 ident: 10.1016/j.compbiomed.2023.107838_bib39 article-title: Hybridizing sine cosine algorithm with differential evolution for global optimization and object tracking publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2017.09.039 – volume: 136 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib61 article-title: Evolutionary warning system for COVID-19 severity: colony predation algorithm enhanced extreme learning machine publication-title: Comput. Biol. Med. doi: 10.1016/j.compbiomed.2021.104698 – year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib84 article-title: Differential evolution-assisted salp swarm algorithm with chaotic structure for real-world problems publication-title: Eng. Comput. – volume: 8 start-page: 35546 year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib28 article-title: Predicting green consumption behaviors of students using efficient firefly grey wolf-assisted K-nearest neighbor classifiers publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2973763 – year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib64 article-title: Chaotic diffusion‐limited aggregation enhanced grey wolf optimizer: insights, analysis, binarization, and feature selection (Intelligent Systems, impact factor:8.709) publication-title: Int. J. Intell. Syst. – volume: 20 start-page: 797 issue: 2 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib57 article-title: Boosting whale optimizer with quasi-oppositional learning and Gaussian barebone for feature selection and COVID-19 image segmentation publication-title: Journal of Bionic Engineering doi: 10.1007/s42235-022-00297-8 – volume: 11 start-page: 341 issue: 4 year: 1997 ident: 10.1016/j.compbiomed.2023.107838_bib33 article-title: Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces – volume: 229 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib27 article-title: An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation publication-title: Knowl. Base Syst. doi: 10.1016/j.knosys.2021.107348 – volume: 243 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib75 article-title: Laplacian Nelder-Mead spherical evolution for parameter estimation of photovoltaic models publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2021.114223 – volume: 146 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib63 article-title: An efficient rotational direction heap-based optimization with orthogonal structure for medical diagnosis publication-title: Comput. Biol. Med. doi: 10.1016/j.compbiomed.2022.105563 – volume: 492 start-page: 181 year: 2019 ident: 10.1016/j.compbiomed.2023.107838_bib40 article-title: Enhanced Moth-flame optimizer with mutation strategy for global optimization publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.04.022 – volume: 20 start-page: 1198 issue: 3 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib58 article-title: Multi-verse optimizer with rosenbrock and diffusion mechanisms for multilevel threshold image segmentation from COVID-19 chest X-ray images publication-title: Journal of Bionic Engineering doi: 10.1007/s42235-022-00295-w – volume: 7 start-page: 26 issue: 1 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib7 article-title: Explainable COVID-19 infections identification and delineation using calibrated pseudo labels publication-title: IEEE Trans. Emerg. Topics Comput. Intellig. doi: 10.1109/TETCI.2022.3189054 – volume: 215 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib41 article-title: Dimension decided Harris hawks optimization with Gaussian mutation: balance analysis and diversity patterns publication-title: Knowl. Base Syst. doi: 10.1016/j.knosys.2020.106425 – volume: 1 start-page: 67 issue: 1 year: 1997 ident: 10.1016/j.compbiomed.2023.107838_bib44 article-title: No free lunch theorems for optimization – volume: 138 year: 2019 ident: 10.1016/j.compbiomed.2023.107838_bib69 article-title: Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.07.031 – volume: 113 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib86 article-title: Differential evolution with rankings-based fitness function for constrained optimization problems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2021.108016 – volume: 76 start-page: 1 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib8 article-title: A critic evaluation of methods for covid-19 automatic detection from x-ray images publication-title: Inf. Fusion doi: 10.1016/j.inffus.2021.04.008 – volume: 95 start-page: 51 year: 2016 ident: 10.1016/j.compbiomed.2023.107838_bib34 article-title: The whale optimization algorithm publication-title: Adv. Eng. Software doi: 10.1016/j.advengsoft.2016.01.008 – volume: 97 start-page: 849 year: 2019 ident: 10.1016/j.compbiomed.2023.107838_bib35 article-title: Harris hawks optimization: algorithm and applications publication-title: Future Generat. Comput. Syst. doi: 10.1016/j.future.2019.02.028 – volume: 19 start-page: 1830 issue: 6 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib48 article-title: Multi-strategies boosted mutative crow search algorithm for global tasks: cases of continuous and discrete optimization publication-title: Journal of Bionic Engineering doi: 10.1007/s42235-022-00228-7 – volume: 18 start-page: 991 issue: 4 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib50 article-title: Generalized oppositional Moth flame optimization with crossover strategy: an approach for medical diagnosis publication-title: Journal of Bionic Engineering doi: 10.1007/s42235-021-0068-1 – volume: 171 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib72 article-title: Memetic Harris Hawks Optimization: developments and perspectives on project scheduling and QoS-aware web service composition publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.114529 – volume: 27 start-page: 18991 issue: 24 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib24 article-title: A non-entropy-based optimal multilevel threshold selection technique for COVID-19 X-ray images using chance-based birds' intelligence publication-title: Soft Comput. doi: 10.1007/s00500-023-08135-7 – volume: 532 start-page: 183 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib13 article-title: RIME: a physics-based optimization publication-title: Neurocomputing doi: 10.1016/j.neucom.2023.02.010 – volume: 32 start-page: 1775 issue: 3 year: 2017 ident: 10.1016/j.compbiomed.2023.107838_bib81 article-title: A novel object tracking algorithm by fusing color and depth information based on single valued neutrosophic cross-entropy publication-title: J. Intell. Fuzzy Syst. doi: 10.3233/JIFS-152381 – volume: 20 start-page: 1296 issue: 3 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib51 article-title: A boosted communicational salp swarm algorithm: performance optimization and comprehensive analysis publication-title: Journal of Bionic Engineering doi: 10.1007/s42235-022-00304-y – year: 2005 ident: 10.1016/j.compbiomed.2023.107838_bib56 article-title: A non-local algorithm for image denoising – year: 2005 ident: 10.1016/j.compbiomed.2023.107838_bib36 – year: 2020 ident: 10.1016/j.compbiomed.2023.107838_bib60 – volume: 11 year: 2021 ident: 10.1016/j.compbiomed.2023.107838_bib3 article-title: Evaluating cancer-related biomarkers based on pathological images: a systematic review publication-title: Front. Oncol. doi: 10.3389/fonc.2021.763527 – volume: 213 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib62 article-title: Gradient-based optimizer improved by Slime Mould Algorithm for global optimization and feature selection for diverse computation problems publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2022.118872 – volume: 185 start-page: 1155 issue: 3 year: 2008 ident: 10.1016/j.compbiomed.2023.107838_bib65 article-title: Ant colony optimization for continuous domains publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2006.06.046 – volume: 81 year: 2019 ident: 10.1016/j.compbiomed.2023.107838_bib45 article-title: Spherical evolution for solving continuous optimization problems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2019.105499 – start-page: 65 year: 2010 ident: 10.1016/j.compbiomed.2023.107838_bib88 article-title: A new metaheuristic bat-inspired algorithm – volume: 17 year: 2023 ident: 10.1016/j.compbiomed.2023.107838_bib23 article-title: An enhanced ant colony optimizer with Cauchy-Gaussian fusion and novel movement strategy for multi-threshold COVID-19 X-ray image segmentation publication-title: Front. Neuroinf. doi: 10.3389/fninf.2023.1126783 – volume: 148 year: 2022 ident: 10.1016/j.compbiomed.2023.107838_bib71 article-title: Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation publication-title: Comput. Biol. Med. doi: 10.1016/j.compbiomed.2022.105810 – volume: 89 start-page: 228 year: 2015 ident: 10.1016/j.compbiomed.2023.107838_bib30 article-title: Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm publication-title: Knowl. Base Syst. doi: 10.1016/j.knosys.2015.07.006 – year: 2016 ident: 10.1016/j.compbiomed.2023.107838_bib14 – start-page: 138 year: 2019 ident: 10.1016/j.compbiomed.2023.107838_bib82 article-title: A hybrid of genetic transform and hyper-rectangle search strategies for evolutionary multi-tasking publication-title: Expert Syst. Appl. |
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| SubjectTerms | Adaptability Algorithms Basic converters Benchmark Convergence Coronaviruses COVID-19 COVID-19 Testing Dispersion Efficiency Entropy Experiments Foraging behavior Global optimization Humans Hunting Image enhancement Image processing Image segmentation Intelligence Internal Medicine Medical diagnosis Methods Optimization algorithms Other Population-based method RIME Searching Signal to noise ratio Swarm intelligence X-Rays |
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| Title | CDRIME-MTIS: An enhanced rime optimization-driven multi-threshold segmentation for COVID-19 X-ray images |
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