{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T15:38:19Z","timestamp":1771256299212,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006261","name":"Taif University","doi-asserted-by":"publisher","award":["TURSP-2020\/313"],"award-info":[{"award-number":["TURSP-2020\/313"]}],"id":[{"id":"10.13039\/501100006261","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Early identification of melanocytic skin lesions increases the survival rate for skin cancer patients. Automated melanocytic skin lesion extraction from dermoscopic images using the computer vision approach is a challenging task as the lesions present in the image can be of different colors, there may be a variation of contrast near the lesion boundaries, lesions may have different sizes and shapes, etc. Therefore, lesion extraction from dermoscopic images is a fundamental step for automated melanoma identification. In this article, a watershed transform based on the fast fuzzy c-means (FCM) clustering algorithm is proposed for the extraction of melanocytic skin lesion from dermoscopic images. Initially, the proposed method removes the artifacts from the dermoscopic images and enhances the texture regions. Further, it is filtered using a Gaussian filter and a local variance filter to enhance the lesion boundary regions. Later, the watershed transform based on MMLVR (multiscale morphological local variance reconstruction) is introduced to acquire the superpixels of the image with accurate boundary regions. Finally, the fast FCM clustering technique is implemented in the superpixels of the image to attain the final lesion extraction result. The proposed method is tested in the three publicly available skin lesion image datasets, i.e., ISIC 2016, ISIC 2017 and ISIC 2018. Experimental evaluation shows that the proposed method achieves a good result.<\/jats:p>","DOI":"10.3390\/sym13112085","type":"journal-article","created":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T21:57:49Z","timestamp":1635976669000},"page":"2085","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Skin Lesion Extraction Using Multiscale Morphological Local Variance Reconstruction Based Watershed Transform and Fast Fuzzy C-Means Clustering"],"prefix":"10.3390","volume":"13","author":[{"given":"Ranjita","family":"Rout","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering, GIET University, Rayagada 765022, Odisha, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6071-764X","authenticated-orcid":false,"given":"Priyadarsan","family":"Parida","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, GIET University, Rayagada 765022, Odisha, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0840-1867","authenticated-orcid":false,"given":"Youseef","family":"Alotaibi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}]},{"given":"Saleh","family":"Alghamdi","sequence":"additional","affiliation":[{"name":"Department of Information Technology, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4750-8384","authenticated-orcid":false,"given":"Osamah Ibrahim","family":"Khalaf","sequence":"additional","affiliation":[{"name":"Al-Nahrain Nanorenewable Energy Research Center, Al-Nahrain University, Baghdad 64074, Iraq"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.patcog.2016.10.031","article-title":"A simple weighted thresholding method for the segmentation of pigmented skin lesions in macroscopic images","volume":"64","author":"Zortea","year":"2017","journal-title":"Pattern Recognit."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/S0010-4825(97)00020-6","article-title":"Dullrazor\u00ae: A software approach to hair removal from images","volume":"27","author":"Lee","year":"1997","journal-title":"Comput. 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