Batuhan Albayrak, M. Darici, Furkan Kiraci, A. S. Öǧrencí, A. Özmen, Kerem Ertez
{"title":"Orak Hücreli Anemi Tespiti Sickle Cell Anemia Detection","authors":"Batuhan Albayrak, M. Darici, Furkan Kiraci, A. S. Öǧrencí, A. Özmen, Kerem Ertez","doi":"10.1109/TIPTEKNO.2018.8597092","DOIUrl":null,"url":null,"abstract":"Anemia is a common name given to falls in oxygen transport capacity due to some of the functional disadvantages of red blood cells. Pathology Laboratorians put the tissue on the microscope glass and try to diagnose Anemia disease. Processes have been taken for a long time and it has been caused to distract. Therefore it has been caused to misdiagnose the Laboratorian. This work shortens the diagnostic period of the disease and to minimizes error probability of this diagnosis by extracting healthy cells and just having sickle cells on the blood tissue using Image Processing Algorithms with an accuracy of 91.11 %, precision of 92.9 %, recall of 79.05 % for Sickle Cell Anemia.","PeriodicalId":127364,"journal":{"name":"2018 Medical Technologies National Congress (TIPTEKNO)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Medical Technologies National Congress (TIPTEKNO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIPTEKNO.2018.8597092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Anemia is a common name given to falls in oxygen transport capacity due to some of the functional disadvantages of red blood cells. Pathology Laboratorians put the tissue on the microscope glass and try to diagnose Anemia disease. Processes have been taken for a long time and it has been caused to distract. Therefore it has been caused to misdiagnose the Laboratorian. This work shortens the diagnostic period of the disease and to minimizes error probability of this diagnosis by extracting healthy cells and just having sickle cells on the blood tissue using Image Processing Algorithms with an accuracy of 91.11 %, precision of 92.9 %, recall of 79.05 % for Sickle Cell Anemia.
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