Exploring Edge-Based Segmentation Towards Automated Skin Lesion Diagnosis

Automated medical diagnosis has many potentials and benefits to support healthcare. Therefore, there is growing number of research on this topic. There are many challenges before automated medical diagnosis is accepted by the healthcare industry and the public as a tool to facilitate healthcare prof...

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Bibliographic Details
Main Authors: Lau, Hui Keng, Chang, Jia Woei, Norhayati Daut, Asni Tahir, Erdah Samino, Mohd Hanafi Bin Ahmad Hijazi
Format: Article
Language:English
Published: American Scientific Publishers 2018
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/23879/1/Exploring%20Edge-Based%20Segmentation%20Towards%20Automated%20Skin%20Lesion%20Diagnosis.pdf
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Summary:Automated medical diagnosis has many potentials and benefits to support healthcare. Therefore, there is growing number of research on this topic. There are many challenges before automated medical diagnosis is accepted by the healthcare industry and the public as a tool to facilitate healthcare professionals. In this paper, initial work on exploring edge-based segmentation algorithms to identify areas on an image that form the skin lesion is presented. Four edge-segmentation operators namely Canny, Prewitt, Sobel, and Roberts were tested using images from online image database. Experiments show results with mixed accuracy depending on the quality of image as well as the pattern of the skin lesions.