Mohendra Roy, Dongmin Seo, Jaewoo Kim, S. Seo, Sangwoo Oh
{"title":"基于智能手机的自动微粒分析系统","authors":"Mohendra Roy, Dongmin Seo, Jaewoo Kim, S. Seo, Sangwoo Oh","doi":"10.1109/C3IT.2015.7060226","DOIUrl":null,"url":null,"abstract":"Cell and microparticle analysis is one of the major task in all pathological labs. The concentration profile, such as red blood cell (RBC), white blood cell (WBC), platelet concentration are the key parameters for early diagnosis of many diseases. However in most laboratories, especially in resource limited settings, this diagnosis are done manually using conventional optical microscope. This manual process is slow and prone to subjective error. In this paper we demonstrate a smartphone based automated cell detection and counting system. The system is based on the lens-free imaging method, which is a compact facility made up of inexpensive components. We evaluated the performance of the system as well as smartphone algorithm by evaluating the concentration of the micro particles of different sizes. This results were then compared with the conventional optical microscope result. The correlation coefficients of this comparisons shows a great agreement between the two modalities. This kind of compact system along with the wireless facility would be a good point of care facility in resource limited settings.","PeriodicalId":402311,"journal":{"name":"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Smartphone based automated microparticle analysis system\",\"authors\":\"Mohendra Roy, Dongmin Seo, Jaewoo Kim, S. Seo, Sangwoo Oh\",\"doi\":\"10.1109/C3IT.2015.7060226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cell and microparticle analysis is one of the major task in all pathological labs. The concentration profile, such as red blood cell (RBC), white blood cell (WBC), platelet concentration are the key parameters for early diagnosis of many diseases. However in most laboratories, especially in resource limited settings, this diagnosis are done manually using conventional optical microscope. This manual process is slow and prone to subjective error. In this paper we demonstrate a smartphone based automated cell detection and counting system. The system is based on the lens-free imaging method, which is a compact facility made up of inexpensive components. We evaluated the performance of the system as well as smartphone algorithm by evaluating the concentration of the micro particles of different sizes. This results were then compared with the conventional optical microscope result. The correlation coefficients of this comparisons shows a great agreement between the two modalities. This kind of compact system along with the wireless facility would be a good point of care facility in resource limited settings.\",\"PeriodicalId\":402311,\"journal\":{\"name\":\"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/C3IT.2015.7060226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/C3IT.2015.7060226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Smartphone based automated microparticle analysis system
Cell and microparticle analysis is one of the major task in all pathological labs. The concentration profile, such as red blood cell (RBC), white blood cell (WBC), platelet concentration are the key parameters for early diagnosis of many diseases. However in most laboratories, especially in resource limited settings, this diagnosis are done manually using conventional optical microscope. This manual process is slow and prone to subjective error. In this paper we demonstrate a smartphone based automated cell detection and counting system. The system is based on the lens-free imaging method, which is a compact facility made up of inexpensive components. We evaluated the performance of the system as well as smartphone algorithm by evaluating the concentration of the micro particles of different sizes. This results were then compared with the conventional optical microscope result. The correlation coefficients of this comparisons shows a great agreement between the two modalities. This kind of compact system along with the wireless facility would be a good point of care facility in resource limited settings.