天美传媒

ISSN: 2476-2067

Toxicology: 天美传媒 Access
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  • Mini Review   
  • Toxicol 天美传媒 Access 2023, Vol 9(5): 233
  • DOI: 10.4172/2476-2067.1000233

Advancing Melanoma Diagnosis Skin Lesion Segmentation Utilizing Perceptual Colour Difference Saliency and Morphological Analysis

Mario Sawarng*
Department of Toxicology, Aga Khan University, Pakistan
*Corresponding Author : Mario Sawarng, Department of Toxicology, Aga Khan University, Pakistan, Email: mario.sawarng@gmail.com

Received Date: Sep 03, 2023 / Published Date: Sep 30, 2023

Abstract

Melanoma, a highly aggressive form of skin cancer, necessitates early and accurate diagnosis for effective treatment. This paper presents an innovative approach to melanoma diagnosis through skin lesion segmentation. Leveraging the synergistic potential of perceptual color difference saliency and morphological analysis, our proposed method aims to enhance the precision of melanoma lesion identification. By harnessing advanced artificial intelligence algorithms, we demonstrate the capability of automated lesion segmentation, enabling clinicians to discern malignancies from healthy tissue with heightened accuracy. This research contributes to the growing field of medical image analysis, providing a robust framework for improving melanoma diagnosis and patient outcomes.

Citation: Sawarng M (2023) Advancing Melanoma Diagnosis Skin LesionSegmentation Utilizing Perceptual Colour Difference Saliency and MorphologicalAnalysis. Toxicol 天美传媒 Access 9: 233. Doi: 10.4172/2476-2067.1000233

Copyright: © 2023 Sawarng M. This is an open-access article distributed underthe terms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original author andsource are credited.

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