{"title":"Estimation of hemoglobin using AI technique","authors":"Suhas B. Dhoke, Anil R. Karwankar, V. Ratnaparkhe","doi":"10.1109/ICISIM.2017.8122147","DOIUrl":null,"url":null,"abstract":"Anemia is a condition in which the hemoglobin (Hb) content becomes less than that of the normal value. In this project, hemoglobin value is estimated using ANN (Artificial Neural Network). Database of blood sample images and their actual Hb values is collected from a local laboratory. Red, green and blue normalized values of images' samples are fed to the ANN as input. Cyanemethemoglobin method based calculated values of Hb obtained from the laboratory are given as output. Comparing the outputs of ANN model results with actual Hb values, accuracy of the network is calculated. This paper covers comparison of performance of different types of Neural Networks for carrying out the stipulated task. It is observed that there is a strong relation between red, green and blue color components of the image with the hemoglobin content of the blood.","PeriodicalId":139000,"journal":{"name":"2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISIM.2017.8122147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Anemia is a condition in which the hemoglobin (Hb) content becomes less than that of the normal value. In this project, hemoglobin value is estimated using ANN (Artificial Neural Network). Database of blood sample images and their actual Hb values is collected from a local laboratory. Red, green and blue normalized values of images' samples are fed to the ANN as input. Cyanemethemoglobin method based calculated values of Hb obtained from the laboratory are given as output. Comparing the outputs of ANN model results with actual Hb values, accuracy of the network is calculated. This paper covers comparison of performance of different types of Neural Networks for carrying out the stipulated task. It is observed that there is a strong relation between red, green and blue color components of the image with the hemoglobin content of the blood.
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