Literature DB >> 31228313

Improved skin lesion edge detection method using Ant Colony Optimization.

Sudhriti Sengupta1, Neetu Mittal1, Megha Modi2.   

Abstract

BACKGROUND: Skin lesion edge detection is a significant step in developing an automatized diagnostic system. The efficient diagnostic system leads to correct identification and detection of skin lesion diseases. In this paper, ant colony optimization (ACO) technique is used to improve the edge contour of skin lesion images. MATERIAL AND
METHOD: Firstly, a three-stage preprocessing methodology involving color space conversion, contrast enhancement, and filtering is applied to improve the skin lesion image quality. The edge map is obtained by applying three types of conventional edge detection methods namely Canny, Sobel, and Prewitt. Thereafter, ACO is applied on these images to produce an improved edge contour. RESULT: The improvement of the proposed methodology is quantitatively verified by analysis of the entropy of the final image obtained by conventional and proposed techniques.
CONCLUSION: From the result analysis, we can conclude that introduction of ACO has increased the efficiency of the conventional edge detection method in skin lesion images.
© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  Ant Colony Optimization; Canny; Prewitt; Sobel; edge detection; skin lesions

Mesh:

Year:  2019        PMID: 31228313     DOI: 10.1111/srt.12744

Source DB:  PubMed          Journal:  Skin Res Technol        ISSN: 0909-752X            Impact factor:   2.365


  1 in total

1.  Edge Detection Algorithm-Based Lung Ultrasound in Evaluation of Efficacy of High-Flow Oxygen Therapy on Critical Lung Injury.

Authors:  Wei Lu; Bin Xie; Zhaolei Ding
Journal:  Comput Math Methods Med       Date:  2022-01-25       Impact factor: 2.238

  1 in total

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