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Proceedings Paper

Automatic layer segmentation of H&E microscopic images of mice skin
Author(s): Saif Hussein; Joanne Selway; Sabah Jassim; Hisham Al-Assam
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Paper Abstract

Mammalian skin is a complex organ composed of a variety of cells and tissue types. The automatic detection and quantification of changes in skin structures has a wide range of applications for biological research. To accurately segment and quantify nuclei, sebaceous gland, hair follicles, and other skin structures, there is a need for a reliable segmentation of different skin layers. This paper presents an efficient segmentation algorithm to segment the three main layers of mice skin, namely epidermis, dermis, and subcutaneous layers. It also segments the epidermis layer into two sub layers, basal and cornified layers. The proposed algorithm uses adaptive colour deconvolution technique on H&E stain images to separate different tissue structures, inter-modes and Otsu thresholding techniques were effectively combined to segment the layers. It then uses a set of morphological and logical operations on each layer to removing unwanted objects. A dataset of 7000 H&E microscopic images of mutant and wild type mice were used to evaluate the effectiveness of the algorithm. Experimental results examined by domain experts have confirmed the viability of the proposed algorithms.

Paper Details

Date Published: 19 May 2016
PDF: 10 pages
Proc. SPIE 9869, Mobile Multimedia/Image Processing, Security, and Applications 2016, 98690C (19 May 2016); doi: 10.1117/12.2224521
Show Author Affiliations
Saif Hussein, The Univ. of Buckingham (United Kingdom)
Joanne Selway, The Univ. of Buckingham (United Kingdom)
Sabah Jassim, The Univ. of Buckingham (United Kingdom)
Hisham Al-Assam, The Univ. of Buckingham (United Kingdom)

Published in SPIE Proceedings Vol. 9869:
Mobile Multimedia/Image Processing, Security, and Applications 2016
Sos S. Agaian; Sabah A. Jassim, Editor(s)

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