IEEE J Biomed Health Inform - Automated segmentation of the melanocytes in skin histopathological images.

Tópicos

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Resumo

In the diagnosis of skin melanoma by analyzing histopathological images, the detection of the melanocytes in the epidermis area is an important step. However, the detection of melanocytes in the epidermis area is dicult because other keratinocytes that are very similar to the melanocytes are also present. This paper proposes a novel computer-aided technique for segmentation of the melanocytes in the skin histopathological images. In order to reduce the local intensity variant, a mean-shift algorithm is applied for the initial segmentation of the image. A local region recursive segmentation algorithm is then proposed to filter out the candidate nuclei regions based on the domain prior knowledge. To distinguish the melanocytes from other keratinocytes in the epidermis area, a novel descriptor, named local double ellipse descriptor (LDED), is proposed to measure the local features of the candidate regions. The LDED uses two parameters: region ellipticity and local pattern characteristics to distinguish the melanocytes from the candidate nuclei regions. Experimental results on 28 dierent histopathological images of skin tissue with dierent zooming factors show that the proposed technique provides a superior performance.

Resumo Limpo

diagnosi skin melanoma analyz histopatholog imag detect melanocyt epidermi area import step howev detect melanocyt epidermi area dicult keratinocyt similar melanocyt also present paper propos novel computeraid techniqu segment melanocyt skin histopatholog imag order reduc local intens variant meanshift algorithm appli initi segment imag local region recurs segment algorithm propos filter candid nuclei region base domain prior knowledg distinguish melanocyt keratinocyt epidermi area novel descriptor name local doubl ellips descriptor lded propos measur local featur candid region lded use two paramet region ellipt local pattern characterist distinguish melanocyt candid nuclei region experiment result dierent histopatholog imag skin tissu dierent zoom factor show propos techniqu provid superior perform

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