Kan Throngnumchai, Pitchayakorn Lomvisai, Chayanan Tantasirin, P. Phasukkit
{"title":"Classification of White blood cell using Deep Convolutional Neural Network","authors":"Kan Throngnumchai, Pitchayakorn Lomvisai, Chayanan Tantasirin, P. Phasukkit","doi":"10.1109/BMEiCON47515.2019.8990301","DOIUrl":null,"url":null,"abstract":"White blood cells are the one of immune system that are involved in protecting the body against infection disease and foreign invaders. There are difference category of white blood cell and each category can indicate about the irregularity of body. Nowadays, White blood cell diagnosis is usually examined manually by doctor. This process consumes a lot time, cost and susceptible to error compare with automatic computerize process. An automatic classification technique for microscopic white blood cell images focusing on images from fresh blood smears[1] is proposed in this paper. The classification is conducted using a proposed method that consist of deep convolutional neural network (DCNN). 10,000 Microscopic blood images were tested and the classification method obtain 93%","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th Biomedical Engineering International Conference (BMEiCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEiCON47515.2019.8990301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
White blood cells are the one of immune system that are involved in protecting the body against infection disease and foreign invaders. There are difference category of white blood cell and each category can indicate about the irregularity of body. Nowadays, White blood cell diagnosis is usually examined manually by doctor. This process consumes a lot time, cost and susceptible to error compare with automatic computerize process. An automatic classification technique for microscopic white blood cell images focusing on images from fresh blood smears[1] is proposed in this paper. The classification is conducted using a proposed method that consist of deep convolutional neural network (DCNN). 10,000 Microscopic blood images were tested and the classification method obtain 93%