Open AccessAutomated segmentation of the epidermis area in skin whole slide histopathological images
Author(s) -
Lu Cheng,
Ma Zhen,
Mandal Mrinal
Publication year - 2015
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2014.0192
Subject(s) - thresholding , computer science , segmentation , artificial intelligence , computer vision , magnification , image segmentation , pattern recognition (psychology) , template matching , epidermis (zoology) , computer aided diagnosis , image (mathematics) , medicine , anatomy
With the development of high‐speed, high‐resolution whole slide histology digital scanners, glass slides of tissue specimen can now be digitised at high magnification to create the whole slide image. Quantitative image analysis tools are then desirable to help the pathologist for their routine examination. Epidermis area is a very important observation area for the cancer diagnosis. Therefore, in order to build up a computer‐aided diagnosis system, segmentation of the epidermis area is often the very first and crucial step. An improved computer‐aided epidermis segmentation technique for the whole slide skin histopathological image is proposed in this study. The proposed technique first obtains an initial segmentation result with the help of global thresholding and shape analysis. A template matching method, with adaptive template intensity value, is then applied. Finally, a threshold is calculated based on the probability density function of the response value image. Experimental results show that the proposed technique overcomes the limitation of the existing technique and provides superior performance, with sensitivity of 95.68%, specificity of 99.41% and precision of 93.13%. The performance of the proposed technique is satisfactory for future clinical use.