M. S. Andrade, F. Cordeiro, V. Macário, Fabiana F. Lima, Suy F. Hwang, Julyanne C. G. Mendonca
{"title":"A Fuzzy-Adaptive Approach to Segment Metaphase Chromosome Images","authors":"M. S. Andrade, F. Cordeiro, V. Macário, Fabiana F. Lima, Suy F. Hwang, Julyanne C. G. Mendonca","doi":"10.1109/BRACIS.2018.00057","DOIUrl":null,"url":null,"abstract":"Chromosome analysis is an important task to detect genetic diseases. However, the process of identifying chromosomes can be very time-consuming. Therefore, the use of an automatic process to detect chromosomes is an important step to aid the diagnosis. The proposed work develop a new approach to automatize the segmentation of chromosomes, using adaptive thresholding combined with fuzzy logic. The proposed method is evaluated using the database from CRCN-NE, which has 35 images. Results showed that the proposed approach compared with state of the art techniques obtained better segmentation results, with sensitivity and specificity values of 91% and 92%, respectively.","PeriodicalId":405190,"journal":{"name":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BRACIS.2018.00057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Chromosome analysis is an important task to detect genetic diseases. However, the process of identifying chromosomes can be very time-consuming. Therefore, the use of an automatic process to detect chromosomes is an important step to aid the diagnosis. The proposed work develop a new approach to automatize the segmentation of chromosomes, using adaptive thresholding combined with fuzzy logic. The proposed method is evaluated using the database from CRCN-NE, which has 35 images. Results showed that the proposed approach compared with state of the art techniques obtained better segmentation results, with sensitivity and specificity values of 91% and 92%, respectively.