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Proceedings Paper

Automatic evaluation of skin histopathological images for melanocytic features
Author(s): Mohaddeseh Koosha; S. Pourya Hoseini Alinodehi; Mircea Nicolescu; Zahra Safaei Naraghi
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Paper Abstract

Successfully detecting melanocyte cells in the skin epidermis has great significance in skin histopathology. Because of the existence of cells with similar appearance to melanocytes in hematoxylin and eosin (HE) images of the epidermis, detecting melanocytes becomes a challenging task. This paper proposes a novel technique for the detection of melanocytes in HE images of the epidermis, based on the melanocyte color features, in the HSI color domain. Initially, an effective soft morphological filter is applied to the HE images in the HSI color domain to remove noise. Then a novel threshold-based technique is applied to distinguish the candidate melanocytes’ nuclei. Similarly, the method is applied to find the candidate surrounding halos of the melanocytes. The candidate nuclei are associated with their surrounding halos using the suggested logical and statistical inferences. Finally, a fuzzy inference system is proposed, based on the HSI color information of a typical melanocyte in the epidermis, to calculate the similarity ratio of each candidate cell to a melanocyte. As our review on the literature shows, this is the first method evaluating epidermis cells for melanocyte similarity ratio. Experimental results on various images with different zooming factors show that the proposed method improves the results of previous works.

Paper Details

Date Published: 1 March 2017
PDF: 7 pages
Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 1014006 (1 March 2017); doi: 10.1117/12.2255002
Show Author Affiliations
Mohaddeseh Koosha, Amirkabir Univ. of Technology (Iran, Islamic Republic of)
S. Pourya Hoseini Alinodehi, Univ. of Nevada, Reno (United States)
Mircea Nicolescu, Univ. of Nevada, Reno (United States)
Zahra Safaei Naraghi, Tehran Univ. of Medical Sciences (Iran, Islamic Republic of)


Published in SPIE Proceedings Vol. 10140:
Medical Imaging 2017: Digital Pathology
Metin N. Gurcan; John E. Tomaszewski, Editor(s)

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