{"title":"Segmentation and analysis of leg ulcers color images","authors":"A. Perez, A. Gonzaga, J. M. Alves","doi":"10.1109/MIAR.2001.930300","DOIUrl":null,"url":null,"abstract":"This paper presents a methodology for the segmentation and analysis of the tissues in color images of leg ulcers. The segmentation is obtained through an automatic analysis made in the RGB and SI channels by changing from the RGB color space to the HSI color space. The aim is to determine which of the five channels have the characteristic that will make the segmentation process more efficient. After the analysis, the selected channel is segmented and used as a mask over the original image, allowing that only the inner tissues of the wound be analyzed. The analysis is done through predetermined functions that attribute membership grade for each processed pixel as well as its level of engagement in a specified tissue class. The article also shows the results obtained from both the segmentation and analysis of tissues using the proposed method.","PeriodicalId":375408,"journal":{"name":"Proceedings International Workshop on Medical Imaging and Augmented Reality","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings International Workshop on Medical Imaging and Augmented Reality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIAR.2001.930300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 52
Abstract
This paper presents a methodology for the segmentation and analysis of the tissues in color images of leg ulcers. The segmentation is obtained through an automatic analysis made in the RGB and SI channels by changing from the RGB color space to the HSI color space. The aim is to determine which of the five channels have the characteristic that will make the segmentation process more efficient. After the analysis, the selected channel is segmented and used as a mask over the original image, allowing that only the inner tissues of the wound be analyzed. The analysis is done through predetermined functions that attribute membership grade for each processed pixel as well as its level of engagement in a specified tissue class. The article also shows the results obtained from both the segmentation and analysis of tissues using the proposed method.