Diagnotic support system of melanoma based on morphological features

Toshiyuki Tanaka; Reina Yamada; Michiko Tanaka; Kunio Shimizu; Masaru Tanaka

doi:10.1541/ieejeiss.127.330

Diagnotic support system of melanoma based on morphological features

Toshiyuki Tanaka, Reina Yamada, Michiko Tanaka, Kunio Shimizu, Masaru Tanaka

Department of Applied Physics and Physico-Informatics

Research output: Contribution to journal › Article › peer-review

Abstract

At present the diagnosis of melanoma is mainly performed based on the experience of each doctor. They need some objective measure for diagnosis of melanoma and nevus. But there are few researches on index for the diagnosis. This study deals with features of melanoma and nevus for computer diagnosis. First, we extracted the contour of lesions by image processing. One hundred five values of features were computed based on ABCD-rule. Discriminant analysis showed the accuracy of 96.0% (Specificity of 98.3% and the Sensitivity of 90.0%). The results obviously showed the difference between melanoma and nevus.

Original language	English
Pages (from-to)	330-337
Number of pages	8
Journal	IEEJ Transactions on Electronics, Information and Systems
Volume	127
Issue number	3
DOIs	https://doi.org/10.1541/ieejeiss.127.330
Publication status	Published - 2007

Keywords

Benign nevus
Discriminant analysis
Image processing
Melanoma

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1541/ieejeiss.127.330

Cite this

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title = "Diagnotic support system of melanoma based on morphological features",

abstract = "At present the diagnosis of melanoma is mainly performed based on the experience of each doctor. They need some objective measure for diagnosis of melanoma and nevus. But there are few researches on index for the diagnosis. This study deals with features of melanoma and nevus for computer diagnosis. First, we extracted the contour of lesions by image processing. One hundred five values of features were computed based on ABCD-rule. Discriminant analysis showed the accuracy of 96.0% (Specificity of 98.3% and the Sensitivity of 90.0%). The results obviously showed the difference between melanoma and nevus.",

keywords = "Benign nevus, Discriminant analysis, Image processing, Melanoma",

author = "Toshiyuki Tanaka and Reina Yamada and Michiko Tanaka and Kunio Shimizu and Masaru Tanaka",

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T1 - Diagnotic support system of melanoma based on morphological features

AU - Tanaka, Toshiyuki

AU - Yamada, Reina

AU - Tanaka, Michiko

AU - Shimizu, Kunio

AU - Tanaka, Masaru

PY - 2007

Y1 - 2007

N2 - At present the diagnosis of melanoma is mainly performed based on the experience of each doctor. They need some objective measure for diagnosis of melanoma and nevus. But there are few researches on index for the diagnosis. This study deals with features of melanoma and nevus for computer diagnosis. First, we extracted the contour of lesions by image processing. One hundred five values of features were computed based on ABCD-rule. Discriminant analysis showed the accuracy of 96.0% (Specificity of 98.3% and the Sensitivity of 90.0%). The results obviously showed the difference between melanoma and nevus.

AB - At present the diagnosis of melanoma is mainly performed based on the experience of each doctor. They need some objective measure for diagnosis of melanoma and nevus. But there are few researches on index for the diagnosis. This study deals with features of melanoma and nevus for computer diagnosis. First, we extracted the contour of lesions by image processing. One hundred five values of features were computed based on ABCD-rule. Discriminant analysis showed the accuracy of 96.0% (Specificity of 98.3% and the Sensitivity of 90.0%). The results obviously showed the difference between melanoma and nevus.

KW - Benign nevus

KW - Discriminant analysis

KW - Image processing

KW - Melanoma

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Diagnotic support system of melanoma based on morphological features

Abstract

Keywords

ASJC Scopus subject areas

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