Epidermis segmentation in skin histopathological images based on thickness measurement and k-means algorithm
Automatic segmentation of the epidermis area in skin histopathological images is an essential step for computer-aided diagnosis of various skin cancers. This paper presents a robust technique for epidermis segmentation in the whole slide skin histopathological images. The proposed technique first pe...
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| Published in | EURASIP journal on image and video processing Vol. 2015; no. 1; pp. 1 - 14 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Cham
Springer International Publishing
23.06.2015
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1687-5281 1687-5176 1687-5281 |
| DOI | 10.1186/s13640-015-0076-3 |
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| Abstract | Automatic segmentation of the epidermis area in skin histopathological images is an essential step for computer-aided diagnosis of various skin cancers. This paper presents a robust technique for epidermis segmentation in the whole slide skin histopathological images. The proposed technique first performs a coarse epidermis segmentation using global thresholding and shape analysis. The epidermis thickness is then measured by a series of line segments perpendicular to the main axis of the initially segmented epidermis mask. If the segmented epidermis mask has a thickness greater than a predefined threshold, the segmentation is assumed to be inaccurate. A second pass of fine segmentation using k-means algorithm is then carried out over these coarsely segmented result to enhance the performance. Experimental results on 64 different skin histopathological images show that the proposed technique provides a superior performance compared to the existing techniques. |
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| AbstractList | Automatic segmentation of the epidermis area in skin histopathological images is an essential step for computer-aided diagnosis of various skin cancers. This paper presents a robust technique for epidermis segmentation in the whole slide skin histopathological images. The proposed technique first performs a coarse epidermis segmentation using global thresholding and shape analysis. The epidermis thickness is then measured by a series of line segments perpendicular to the main axis of the initially segmented epidermis mask. If the segmented epidermis mask has a thickness greater than a predefined threshold, the segmentation is assumed to be inaccurate. A second pass of fine segmentation using k-means algorithm is then carried out over these coarsely segmented result to enhance the performance. Experimental results on 64 different skin histopathological images show that the proposed technique provides a superior performance compared to the existing techniques. |
| ArticleNumber | 18 |
| Author | Xu, Hongming Mandal, Mrinal |
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| Cites_doi | 10.1186/1755-8794-6-S3-S10 10.1007/s11265-008-0201-y 10.1109/TITB.2012.2199595 10.1186/1471-2342-6-14 10.1016/j.compmedimag.2011.02.005 10.1002/path.1061 10.1109/TBME.2010.2060336 10.1109/TITB.2007.898006 10.1109/JSTSP.2008.2011157 10.1145/62065.62074 10.3322/caac.21166 10.1016/j.patcog.2008.10.035 10.1109/TBME.2011.2179298 10.1109/JBHI.2013.2297030 10.1016/j.patcog.2008.08.027 10.1186/1471-2342-14-7 10.1016/j.micron.2014.02.001 10.1016/j.patcog.2012.07.020 10.1109/RBME.2009.2034865 10.1109/TITB.2009.2017529 10.1109/34.765658 10.1136/bmj.298.6675.707 10.1109/TBME.2010.2041232 10.1109/EMBC.2012.6347204 10.1007/978-3-642-37311-4 10.1007/978-1-84882-513-0_13 |
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| Copyright | Xu and Mandal. 2015. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Author(s) 2015 |
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| Keywords | Histopathological image analysis Epidermis thickness Global threshold Epidermis segmentation |
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| Snippet | Automatic segmentation of the epidermis area in skin histopathological images is an essential step for computer-aided diagnosis of various skin cancers. This... |
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| SubjectTerms | Algorithms Biometrics Cancer Engineering Epidermis Image processing Image Processing and Computer Vision Masks Pattern Recognition Segmentation Segments Signal,Image and Speech Processing |
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| Title | Epidermis segmentation in skin histopathological images based on thickness measurement and k-means algorithm |
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