Robust navigation support in lowest dose image setting

Purpose Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventi...

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Published in	International journal for computer assisted radiology and surgery Vol. 14; no. 2; pp. 291 - 300
Main Authors	Bui, Mai, Bourier, Felix, Baur, Christoph, Milletari, Fausto, Navab, Nassir, Demirci, Stefanie
Format	Journal Article
Language	English
Published	Cham Springer International Publishing 01.02.2019 Springer Nature B.V
Subjects	Ablation Algorithms Arrhythmia Arrhythmias, Cardiac - diagnosis Cardiac Catheters Catheter Ablation - methods Catheterization Catheters Coding Computer Imaging Computer Science Electrodes Electrophysiologic Techniques, Cardiac - methods Electrophysiology Fluoroscopy Fluoroscopy - methods Ground truth Health Informatics Humans Image enhancement Image setting Imaging Labels Medical imaging Medical personnel Medicine Medicine & Public Health Myocardium Original Article Pattern Recognition and Graphics Perturbation Radiology Robustness Sequences Surgery Tracking Vision X ray imagery Online tracking Electrode tracking Fluoroscopy Online robust PCA Sparse coding Computer-assisted electrophysiology
Online Access	Get full text
ISSN	1861-6410 1861-6429 1861-6429
DOI	10.1007/s11548-018-1874-8

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Abstract	Purpose Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff. Methods In this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on ℓ 1 -sparse coding and online robust PCA (ORPCA) . Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures. Results We have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of 86.9 % . Conclusion Besides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on ℓ 1 -sparse coding and online robust PCA (ORPCA) , our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters.
AbstractList	Purpose Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff. Methods In this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on ℓ 1 -sparse coding and online robust PCA (ORPCA) . Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures. Results We have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of 86.9 % . Conclusion Besides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on ℓ 1 -sparse coding and online robust PCA (ORPCA) , our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters. PurposeClinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff.MethodsIn this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on ℓ1-sparse coding and online robust PCA (ORPCA). Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures.ResultsWe have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of 86.9%.ConclusionBesides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on ℓ1-sparse coding and online robust PCA (ORPCA), our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters. Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff. In this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on [Formula: see text]-sparse coding and online robust PCA (ORPCA). Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures. We have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of [Formula: see text]. Besides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on [Formula: see text]-sparse coding and online robust PCA (ORPCA), our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters. Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff.PURPOSEClinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff.In this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on [Formula: see text]-sparse coding and online robust PCA (ORPCA). Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures.METHODSIn this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on [Formula: see text]-sparse coding and online robust PCA (ORPCA). Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures.We have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of [Formula: see text].RESULTSWe have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of [Formula: see text].Besides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on [Formula: see text]-sparse coding and online robust PCA (ORPCA), our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters.CONCLUSIONBesides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on [Formula: see text]-sparse coding and online robust PCA (ORPCA), our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters.
Author	Milletari, Fausto Navab, Nassir Bui, Mai Demirci, Stefanie Baur, Christoph Bourier, Felix
Author_xml	– sequence: 1 givenname: Mai orcidid: 0000-0002-4509-8473 surname: Bui fullname: Bui, Mai email: mai.bui@tum.de organization: Computer Aided Medical Procedures, Technische Universität München – sequence: 2 givenname: Felix surname: Bourier fullname: Bourier, Felix organization: Deutsches Herzzentrum München – sequence: 3 givenname: Christoph surname: Baur fullname: Baur, Christoph organization: Computer Aided Medical Procedures, Technische Universität München – sequence: 4 givenname: Fausto surname: Milletari fullname: Milletari, Fausto organization: Computer Aided Medical Procedures, Technische Universität München – sequence: 5 givenname: Nassir surname: Navab fullname: Navab, Nassir organization: Computer Aided Medical Procedures, Technische Universität München – sequence: 6 givenname: Stefanie surname: Demirci fullname: Demirci, Stefanie organization: Computer Aided Medical Procedures, Technische Universität München
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Keywords	Online tracking Electrode tracking Fluoroscopy Online robust PCA Sparse coding Computer-assisted electrophysiology
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References	Zoni-BerissoMLercariFCarazzaTDomenicucciSEpidemiology of atrial fibrillation: European perspectiveClin Epidemiol2014621322024966695406495210.2147/CLEP.S47385 FrangiAFNiessenWJVinckenKLViergeverMAWellsWMColchesterADelpSMultiscale vessel enhancement filteringMedical image computing and computer-assisted intervention—MICCAI’981998BerlinSpringer13013710.1007/BFb0056195 GaitaFGuerraPGBattagliaAAnselminoMThe dream of near-zero X-rays ablation comes trueEur Heart J20163736274927552735405310.1093/eurheartj/ehw223 WeickertJScharrHA scheme for coherence-enhancing diffusion filtering with optimized rotation invarianceJ Vis Commun Image Represent2002131–210311810.1006/jvci.2001.0495 VolpiDSarhanMHGhotbiRNavabNMateusDDemirciSOnline tracking of interventional devices for endovascular aortic repairInt J Comput Assist Radiol Surg20151067737812597683210.1007/s11548-015-1217-y CandèsEJLiXMaYWrightJRobust principal component analysis?J ACM20115831110.1145/1970392.1970395 PanayiotouMRhodeKSKingAPMaYCooklinMNeillOMGillJHousdenCAHousdenRJImage-based view-angle independent cardiorespiratory motion gating and coronary sinus catheter tracking for X-ray-guided cardiac electrophysiology proceduresPhys Med Biol2015602080871:CAS:528:DC%2BC28XmtVCgu7o%3D2642586010.1088/0031-9155/60/20/8087 FitzgibbonAPiluMFisherRBDirect least square fitting of ellipsesIEEE Trans Pattern Anal Mach Intell199921547648010.1109/34.765658 WolterinkJMLeinerTViergeverMAIšgumIGenerative adversarial networks for noise reduction in low-dose CTIEEE Trans Med Imaging20173612253625452857434610.1109/TMI.2017.2708987 BourierFReentsTAmmar-BuschSBuiattiAKottmaierMSemmlerVTelishevskaMBrkicAGrebmerCLennerzCKolbCHesslingGDeisenhoferIEvaluation of a new very low dose imaging protocol: feasibility and impact on X-ray dose levels in electrophysiology proceduresEuropace20151891406141026589627540003110.1093/europace/euv364 HariharanSGStrobelNKaethnerCKowarschikMDemirciSAlbarqouniSFahrigRNavabNA photon recycling approach to the denoising of ultra-low dose X-ray sequencesInt J Comput Assist Radiol Surg2018138478542963748610.1007/s11548-018-1746-2 OtsuNA threshold selection method from gray-level histogramsAutomatica197511285–2962327 VaswaniNamrataBouwmansThierryJavedSajidNarayanamurthyPraneethRobust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace RecoveryIEEE Signal Processing Magazine2018354325510.1109/MSP.2018.2826566 CrowhurstJHaqqaniHWrightDWhitbyMLeeABettsJDenmanRUltra low radiation dose during electrophysiology procedures using optimised new generation fluoroscopy technologyPacing Clin Electrophysiol20174089479542861803610.1111/pace.13141 Matviychuk Y, Mailhé B, Chen X, Wang Q, Kiraly A, Strobel N, Nadar M (2016) Learning a multiscale patch-based representation for image denoising in X-ray fluoroscopy. In: 2016 IEEE international conference on image processing (ICIP). IEEE, pp 2330–2334 Milletari F, Belagiannis V, Navab N, Fallavollita P (2014) Fully automatic catheter localization in c-arm images using ℓ1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ell _1$$\end{document}-sparse coding. In: Medical image computing and computer-assisted intervention—MICCAI 2014, Part II, pp 570–577 HongBWeiLHuYCaiDHeXOnline robust principal component analysis via truncated nuclear norm regularizationNeurocomputing201617521622210.1016/j.neucom.2015.10.052 MaYGoginNCathierPHousdenRJGijsbersGCooklinMO’NeillMGillJRinaldiCARazaviRRhodeKSReal-time X-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventionsMed Phys20134070719022382243910.1118/1.4808114 Javed S, Oh SH, Sobral A, Bouwmans T, Jung SK. (2014) OR-PCA with MRF for robust foreground detection in highly dynamic backgrounds. In: Asian conference on computer vision. Springer, pp 284–299 SongWZhuJLiYChenCImage alignment by online robust PCA via stochastic gradient descentIEEE Trans Circuits Syst Video Technol20162671241125010.1109/TCSVT.2015.2455711 Ambrosini P, Ruijters D, Niessen WJ, Moelker A, van Walsum T (2017) Fully automatic and real-time catheter segmentation in X-ray fluoroscopy. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 577–585 BouwmansTZahzahEHRobust PCA via principal component pursuit: a review for a comparative evaluation in video surveillanceComput Vis Image Underst2014122223410.1016/j.cviu.2013.11.009 WuXHousdenJMaYRazaviBRhodeKRueckertDFast catheter segmentation from echocardiographic sequences based on segmentation from corresponding X-ray fluoroscopy for cardiac catheterization interventionsIEEE Trans Med Imaging20153448618762529179010.1109/TMI.2014.2360988 Javed S, Bouwmans T, Jung SK (2017) Improving OR-PCA via smoothed spatially-consistent low-rank modeling for background subtraction. In: Proceedings of the symposium on applied computing. ACM, pp 89–94 AmiotCGirardCChanussotJPescatoreJDesvignesMSpatio-temporal multiscale denoising of fluoroscopic sequenceIEEE Trans Med Imaging2016356156515742681270510.1109/TMI.2016.2520092 Zhan J, Lois B, Guo H, Vaswani, N (2016) Online (and offline) robust PCA: novel algorithms and performance guarantees. In: Artificial intelligence and statistics, pp 1488–1496 CoupéPHellierPKervrannCBarillotCNonlocal means-based speckle filtering for ultrasound imagesIEEE Trans Image Process200918102221222919482578278408110.1109/TIP.2009.2024064 MacleLThibaultBAndradeJGCardiac electrophysiology procedures guided by novel non-fluoroscopic catheter tracking systemsExpert Rev Medl Dev20161343093111:CAS:528:DC%2BC28XjsFemtb0%3D10.1586/17434440.2016.1153969 LoweDGDistinctive image features from scale-invariant keypointsInt J Comput Vis20046029111010.1023/B:VISI.0000029664.99615.94 J Weickert (1874_CR25) 2002; 13 1874_CR13 A Fitzgibbon (1874_CR8) 1999; 21 1874_CR14 W Song (1874_CR22) 2016; 26 T Bouwmans (1874_CR4) 2014; 122 M Panayiotou (1874_CR21) 2015; 60 F Bourier (1874_CR3) 2015; 18 X Wu (1874_CR27) 2015; 34 1874_CR18 L Macle (1874_CR17) 2016; 13 1874_CR19 B Hong (1874_CR12) 2016; 175 D Volpi (1874_CR24) 2015; 10 JM Wolterink (1874_CR26) 2017; 36 DG Lowe (1874_CR15) 2004; 60 M Zoni-Berisso (1874_CR29) 2014; 6 EJ Candès (1874_CR5) 2011; 58 N Otsu (1874_CR20) 1975; 11 C Amiot (1874_CR2) 2016; 35 Y Ma (1874_CR16) 2013; 40 J Crowhurst (1874_CR7) 2017; 40 F Gaita (1874_CR10) 2016; 37 SG Hariharan (1874_CR11) 2018; 13 Namrata Vaswani (1874_CR23) 2018; 35 P Coupé (1874_CR6) 2009; 18 1874_CR28 1874_CR1 AF Frangi (1874_CR9) 1998
References_xml	– reference: Matviychuk Y, Mailhé B, Chen X, Wang Q, Kiraly A, Strobel N, Nadar M (2016) Learning a multiscale patch-based representation for image denoising in X-ray fluoroscopy. In: 2016 IEEE international conference on image processing (ICIP). IEEE, pp 2330–2334 – reference: LoweDGDistinctive image features from scale-invariant keypointsInt J Comput Vis20046029111010.1023/B:VISI.0000029664.99615.94 – reference: MaYGoginNCathierPHousdenRJGijsbersGCooklinMO’NeillMGillJRinaldiCARazaviRRhodeKSReal-time X-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventionsMed Phys20134070719022382243910.1118/1.4808114 – reference: HongBWeiLHuYCaiDHeXOnline robust principal component analysis via truncated nuclear norm regularizationNeurocomputing201617521622210.1016/j.neucom.2015.10.052 – reference: VolpiDSarhanMHGhotbiRNavabNMateusDDemirciSOnline tracking of interventional devices for endovascular aortic repairInt J Comput Assist Radiol Surg20151067737812597683210.1007/s11548-015-1217-y – reference: WeickertJScharrHA scheme for coherence-enhancing diffusion filtering with optimized rotation invarianceJ Vis Commun Image Represent2002131–210311810.1006/jvci.2001.0495 – reference: BourierFReentsTAmmar-BuschSBuiattiAKottmaierMSemmlerVTelishevskaMBrkicAGrebmerCLennerzCKolbCHesslingGDeisenhoferIEvaluation of a new very low dose imaging protocol: feasibility and impact on X-ray dose levels in electrophysiology proceduresEuropace20151891406141026589627540003110.1093/europace/euv364 – reference: Javed S, Oh SH, Sobral A, Bouwmans T, Jung SK. (2014) OR-PCA with MRF for robust foreground detection in highly dynamic backgrounds. In: Asian conference on computer vision. Springer, pp 284–299 – reference: WuXHousdenJMaYRazaviBRhodeKRueckertDFast catheter segmentation from echocardiographic sequences based on segmentation from corresponding X-ray fluoroscopy for cardiac catheterization interventionsIEEE Trans Med Imaging20153448618762529179010.1109/TMI.2014.2360988 – reference: CandèsEJLiXMaYWrightJRobust principal component analysis?J ACM20115831110.1145/1970392.1970395 – reference: AmiotCGirardCChanussotJPescatoreJDesvignesMSpatio-temporal multiscale denoising of fluoroscopic sequenceIEEE Trans Med Imaging2016356156515742681270510.1109/TMI.2016.2520092 – reference: GaitaFGuerraPGBattagliaAAnselminoMThe dream of near-zero X-rays ablation comes trueEur Heart J20163736274927552735405310.1093/eurheartj/ehw223 – reference: FrangiAFNiessenWJVinckenKLViergeverMAWellsWMColchesterADelpSMultiscale vessel enhancement filteringMedical image computing and computer-assisted intervention—MICCAI’981998BerlinSpringer13013710.1007/BFb0056195 – reference: FitzgibbonAPiluMFisherRBDirect least square fitting of ellipsesIEEE Trans Pattern Anal Mach Intell199921547648010.1109/34.765658 – reference: CrowhurstJHaqqaniHWrightDWhitbyMLeeABettsJDenmanRUltra low radiation dose during electrophysiology procedures using optimised new generation fluoroscopy technologyPacing Clin Electrophysiol20174089479542861803610.1111/pace.13141 – reference: MacleLThibaultBAndradeJGCardiac electrophysiology procedures guided by novel non-fluoroscopic catheter tracking systemsExpert Rev Medl Dev20161343093111:CAS:528:DC%2BC28XjsFemtb0%3D10.1586/17434440.2016.1153969 – reference: HariharanSGStrobelNKaethnerCKowarschikMDemirciSAlbarqouniSFahrigRNavabNA photon recycling approach to the denoising of ultra-low dose X-ray sequencesInt J Comput Assist Radiol Surg2018138478542963748610.1007/s11548-018-1746-2 – reference: Ambrosini P, Ruijters D, Niessen WJ, Moelker A, van Walsum T (2017) Fully automatic and real-time catheter segmentation in X-ray fluoroscopy. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 577–585 – reference: Zoni-BerissoMLercariFCarazzaTDomenicucciSEpidemiology of atrial fibrillation: European perspectiveClin Epidemiol2014621322024966695406495210.2147/CLEP.S47385 – reference: Javed S, Bouwmans T, Jung SK (2017) Improving OR-PCA via smoothed spatially-consistent low-rank modeling for background subtraction. In: Proceedings of the symposium on applied computing. ACM, pp 89–94 – reference: BouwmansTZahzahEHRobust PCA via principal component pursuit: a review for a comparative evaluation in video surveillanceComput Vis Image Underst2014122223410.1016/j.cviu.2013.11.009 – reference: WolterinkJMLeinerTViergeverMAIšgumIGenerative adversarial networks for noise reduction in low-dose CTIEEE Trans Med Imaging20173612253625452857434610.1109/TMI.2017.2708987 – reference: CoupéPHellierPKervrannCBarillotCNonlocal means-based speckle filtering for ultrasound imagesIEEE Trans Image Process200918102221222919482578278408110.1109/TIP.2009.2024064 – reference: Milletari F, Belagiannis V, Navab N, Fallavollita P (2014) Fully automatic catheter localization in c-arm images using ℓ1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ell _1$$\end{document}-sparse coding. In: Medical image computing and computer-assisted intervention—MICCAI 2014, Part II, pp 570–577 – reference: PanayiotouMRhodeKSKingAPMaYCooklinMNeillOMGillJHousdenCAHousdenRJImage-based view-angle independent cardiorespiratory motion gating and coronary sinus catheter tracking for X-ray-guided cardiac electrophysiology proceduresPhys Med Biol2015602080871:CAS:528:DC%2BC28XmtVCgu7o%3D2642586010.1088/0031-9155/60/20/8087 – reference: SongWZhuJLiYChenCImage alignment by online robust PCA via stochastic gradient descentIEEE Trans Circuits Syst Video Technol20162671241125010.1109/TCSVT.2015.2455711 – reference: OtsuNA threshold selection method from gray-level histogramsAutomatica197511285–2962327 – reference: Zhan J, Lois B, Guo H, Vaswani, N (2016) Online (and offline) robust PCA: novel algorithms and performance guarantees. In: Artificial intelligence and statistics, pp 1488–1496 – reference: VaswaniNamrataBouwmansThierryJavedSajidNarayanamurthyPraneethRobust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace RecoveryIEEE Signal Processing Magazine2018354325510.1109/MSP.2018.2826566 – volume: 10 start-page: 773 issue: 6 year: 2015 ident: 1874_CR24 publication-title: Int J Comput Assist Radiol Surg doi: 10.1007/s11548-015-1217-y – volume: 37 start-page: 2749 issue: 36 year: 2016 ident: 1874_CR10 publication-title: Eur Heart J doi: 10.1093/eurheartj/ehw223 – volume: 11 start-page: 23 issue: 285–296 year: 1975 ident: 1874_CR20 publication-title: Automatica – volume: 122 start-page: 22 year: 2014 ident: 1874_CR4 publication-title: Comput Vis Image Underst doi: 10.1016/j.cviu.2013.11.009 – volume: 18 start-page: 1406 issue: 9 year: 2015 ident: 1874_CR3 publication-title: Europace doi: 10.1093/europace/euv364 – volume: 21 start-page: 476 issue: 5 year: 1999 ident: 1874_CR8 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.765658 – ident: 1874_CR18 doi: 10.1109/ICIP.2016.7532775 – volume: 60 start-page: 91 issue: 2 year: 2004 ident: 1874_CR15 publication-title: Int J Comput Vis doi: 10.1023/B:VISI.0000029664.99615.94 – volume: 35 start-page: 32 issue: 4 year: 2018 ident: 1874_CR23 publication-title: IEEE Signal Processing Magazine doi: 10.1109/MSP.2018.2826566 – volume: 13 start-page: 103 issue: 1–2 year: 2002 ident: 1874_CR25 publication-title: J Vis Commun Image Represent doi: 10.1006/jvci.2001.0495 – ident: 1874_CR1 doi: 10.1007/978-3-319-66185-8_65 – volume: 58 start-page: 11 issue: 3 year: 2011 ident: 1874_CR5 publication-title: J ACM doi: 10.1145/1970392.1970395 – start-page: 130 volume-title: Medical image computing and computer-assisted intervention—MICCAI’98 year: 1998 ident: 1874_CR9 doi: 10.1007/BFb0056195 – volume: 18 start-page: 2221 issue: 10 year: 2009 ident: 1874_CR6 publication-title: IEEE Trans Image Process doi: 10.1109/TIP.2009.2024064 – volume: 36 start-page: 2536 issue: 12 year: 2017 ident: 1874_CR26 publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2017.2708987 – volume: 13 start-page: 309 issue: 4 year: 2016 ident: 1874_CR17 publication-title: Expert Rev Medl Dev doi: 10.1586/17434440.2016.1153969 – volume: 34 start-page: 861 issue: 4 year: 2015 ident: 1874_CR27 publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2014.2360988 – volume: 35 start-page: 1565 issue: 6 year: 2016 ident: 1874_CR2 publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2016.2520092 – volume: 40 start-page: 071902 issue: 7 year: 2013 ident: 1874_CR16 publication-title: Med Phys doi: 10.1118/1.4808114 – volume: 175 start-page: 216 year: 2016 ident: 1874_CR12 publication-title: Neurocomputing doi: 10.1016/j.neucom.2015.10.052 – volume: 26 start-page: 1241 issue: 7 year: 2016 ident: 1874_CR22 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/TCSVT.2015.2455711 – ident: 1874_CR14 – volume: 40 start-page: 947 issue: 8 year: 2017 ident: 1874_CR7 publication-title: Pacing Clin Electrophysiol doi: 10.1111/pace.13141 – ident: 1874_CR19 doi: 10.1007/978-3-319-10470-6_71 – volume: 13 start-page: 847 year: 2018 ident: 1874_CR11 publication-title: Int J Comput Assist Radiol Surg doi: 10.1007/s11548-018-1746-2 – volume: 6 start-page: 213 year: 2014 ident: 1874_CR29 publication-title: Clin Epidemiol doi: 10.2147/CLEP.S47385 – ident: 1874_CR28 – ident: 1874_CR13 doi: 10.1145/3019612.3019637 – volume: 60 start-page: 8087 issue: 20 year: 2015 ident: 1874_CR21 publication-title: Phys Med Biol doi: 10.1088/0031-9155/60/20/8087
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Snippet	Purpose Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the... Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal... PurposeClinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the...
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SubjectTerms	Ablation Algorithms Arrhythmia Arrhythmias, Cardiac - diagnosis Cardiac Catheters Catheter Ablation - methods Catheterization Catheters Coding Computer Imaging Computer Science Electrodes Electrophysiologic Techniques, Cardiac - methods Electrophysiology Fluoroscopy Fluoroscopy - methods Ground truth Health Informatics Humans Image enhancement Image setting Imaging Labels Medical imaging Medical personnel Medicine Medicine & Public Health Myocardium Original Article Pattern Recognition and Graphics Perturbation Radiology Robustness Sequences Surgery Tracking Vision X ray imagery
Title	Robust navigation support in lowest dose image setting
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