DocumentCode :
740833
Title :
Automated segmentation of the epidermis area in skin whole slide histopathological images
Author :
Cheng Lu ; Zhen Ma ; Mandal, Mrinal
Author_Institution :
Coll. of Comput. Sci., Shaanxi Normal Univ., Xi´an, China
Volume :
9
Issue :
9
fYear :
2015
Firstpage :
735
Lastpage :
742
Abstract :
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.
Keywords :
biomedical optical imaging; cancer; image matching; image resolution; image segmentation; medical image processing; probability; skin; adaptive template intensity value; automated segmentation; cancer diagnosis; computer-aided diagnosis system; computer-aided epidermis segmentation technique; glass slides; high-resolution whole slide histology digital scanners; high-speed whole slide histology digital scanners; pathologist; probability density function; quantitative image analysis; response value image; shape analysis; skin whole slide histopathological images; template matching method; tissue specimen; whole slide skin histopathological image;
fLanguage :
English
Journal_Title :
Image Processing, IET
Publisher :
iet
ISSN :
1751-9659
Type :
jour
DOI :
10.1049/iet-ipr.2014.0192
Filename :
7224104
Link To Document :
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