A Study of Segmentation Techniques for Diagnosing Melanoma in Dermoscopic Images

Volume: 10 | Issue: 01 | Year 2024 | Subscription
International Journal of Image Processing and Pattern Recognition
Received Date: 04/14/2024
Acceptance Date: 04/24/2024
Published On: 2024-05-30
First Page: 1
Last Page: 10

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By: Jasmine Samraj and R. Pavithra

Abstract

Skin cancer remains among the deadliest forms of cancer, with an average survival rate ranging from 18% to 20%. Detecting and segmenting melanoma early is a challenging yet crucial undertaking. To effectively segment the lesions, several studies have presented automated and standard techniques. Likewise, traditional methods for segmentation frequently require inputs from humans and cannot be applied in automated systems. The aim of this article is to provide a comparative analysis of a various number of segmentation methods. The methods are explained along with their benefits and drawbacks. In numerous studies, effective methods for image segmentation of skin lesions have been successfully explored. Therefore, based on an analysis of the various segmentation approaches, intensity-based segmentation performs the best in segmenting the lesion region and produces more accurate findings.

Keywords: Skin cancer, image segmentation, intensity-based segmentation, skin lesions, dermoscopic image

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How to cite this article: Jasmine Samraj and R. Pavithra, A Study of Segmentation Techniques for Diagnosing Melanoma in Dermoscopic Images. International Journal of Image Processing and Pattern Recognition. 2024; 10(01): 1-10p.

How to cite this URL: Jasmine Samraj and R. Pavithra, A Study of Segmentation Techniques for Diagnosing Melanoma in Dermoscopic Images. International Journal of Image Processing and Pattern Recognition. 2024; 10(01): 1-10p. Available from:https://journalspub.com/publication/ijippr-v10i01-6728/
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