Saowaluck Kaewkamnerd, A. Intarapanich, Montri Pannarut, Sastra Chaotheing, C. Uthaipibull, S. Tongsima
{"title":"浆血膜中疟原虫检测分类装置","authors":"Saowaluck Kaewkamnerd, A. Intarapanich, Montri Pannarut, Sastra Chaotheing, C. Uthaipibull, S. Tongsima","doi":"10.1109/IDAACS.2011.6072791","DOIUrl":null,"url":null,"abstract":"In Thailand, malaria diagnosis still relies primarily on microscopic examination of Giemsa-stained thick and thin blood films. However, the method requires vigorously trained technicians to correctly identify the disease, and is known to be error-prone due to human fatigue. The limited number of such technicians further reduces the effectiveness of the attempt to control malaria. Thus, this project aims to develop an automated system to identify and analyze parasite species on thick blood films by image analysis techniques. The system comprises two main components: (1) Image acquisition unit and (2) Image analysis module. In our work, we have developed an image acquisition system that can be easily mounted on most conventional light microscopes. It automatically controls the movement of microscope stage in 3-directional planes. The vertical adjustment (focusing) can be made in a nanometer range (7–9 nm). Images are acquired with a digital camera that is installed at the top of microscope. The captured images are analyzed by our image analysis software which utilizes the state-of-the-art algorithms to detect and identify malaria parasites.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"123 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Detection and classification device for malaria parasites in thick-blood films\",\"authors\":\"Saowaluck Kaewkamnerd, A. Intarapanich, Montri Pannarut, Sastra Chaotheing, C. Uthaipibull, S. Tongsima\",\"doi\":\"10.1109/IDAACS.2011.6072791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Thailand, malaria diagnosis still relies primarily on microscopic examination of Giemsa-stained thick and thin blood films. However, the method requires vigorously trained technicians to correctly identify the disease, and is known to be error-prone due to human fatigue. The limited number of such technicians further reduces the effectiveness of the attempt to control malaria. Thus, this project aims to develop an automated system to identify and analyze parasite species on thick blood films by image analysis techniques. The system comprises two main components: (1) Image acquisition unit and (2) Image analysis module. In our work, we have developed an image acquisition system that can be easily mounted on most conventional light microscopes. It automatically controls the movement of microscope stage in 3-directional planes. The vertical adjustment (focusing) can be made in a nanometer range (7–9 nm). Images are acquired with a digital camera that is installed at the top of microscope. The captured images are analyzed by our image analysis software which utilizes the state-of-the-art algorithms to detect and identify malaria parasites.\",\"PeriodicalId\":106306,\"journal\":{\"name\":\"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems\",\"volume\":\"123 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAACS.2011.6072791\",\"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 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAACS.2011.6072791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection and classification device for malaria parasites in thick-blood films
In Thailand, malaria diagnosis still relies primarily on microscopic examination of Giemsa-stained thick and thin blood films. However, the method requires vigorously trained technicians to correctly identify the disease, and is known to be error-prone due to human fatigue. The limited number of such technicians further reduces the effectiveness of the attempt to control malaria. Thus, this project aims to develop an automated system to identify and analyze parasite species on thick blood films by image analysis techniques. The system comprises two main components: (1) Image acquisition unit and (2) Image analysis module. In our work, we have developed an image acquisition system that can be easily mounted on most conventional light microscopes. It automatically controls the movement of microscope stage in 3-directional planes. The vertical adjustment (focusing) can be made in a nanometer range (7–9 nm). Images are acquired with a digital camera that is installed at the top of microscope. The captured images are analyzed by our image analysis software which utilizes the state-of-the-art algorithms to detect and identify malaria parasites.