{"title":"生物医学成像中主观轮廓的边缘跟踪","authors":"G. Garibotto, V. Garibotto","doi":"10.1109/ICIAP.2007.56","DOIUrl":null,"url":null,"abstract":"The paper describes a method for computer-assisted edge tracking and following by local profile matching. It is used primarily to integrate and support manual selection when complex contours have to be found and identified. Such a requirement is quite common in biomedical applications, including a wide spectrum of image modalities, from histological samples to MRI images. The referred example takes part in the analysis of in vitro receptor auto-radiographic data, for the architectonic characterization of transmitter receptors within a defined cortical region. The practical validation we provide of the proposed tracking model reveals that it is a very promising approach, enabling accurate and fast processing of multiple images.","PeriodicalId":118466,"journal":{"name":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Edge Tracking of subjective contours in Biomedical Imaging\",\"authors\":\"G. Garibotto, V. Garibotto\",\"doi\":\"10.1109/ICIAP.2007.56\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes a method for computer-assisted edge tracking and following by local profile matching. It is used primarily to integrate and support manual selection when complex contours have to be found and identified. Such a requirement is quite common in biomedical applications, including a wide spectrum of image modalities, from histological samples to MRI images. The referred example takes part in the analysis of in vitro receptor auto-radiographic data, for the architectonic characterization of transmitter receptors within a defined cortical region. The practical validation we provide of the proposed tracking model reveals that it is a very promising approach, enabling accurate and fast processing of multiple images.\",\"PeriodicalId\":118466,\"journal\":{\"name\":\"14th International Conference on Image Analysis and Processing (ICIAP 2007)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"14th International Conference on Image Analysis and Processing (ICIAP 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIAP.2007.56\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2007.56","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge Tracking of subjective contours in Biomedical Imaging
The paper describes a method for computer-assisted edge tracking and following by local profile matching. It is used primarily to integrate and support manual selection when complex contours have to be found and identified. Such a requirement is quite common in biomedical applications, including a wide spectrum of image modalities, from histological samples to MRI images. The referred example takes part in the analysis of in vitro receptor auto-radiographic data, for the architectonic characterization of transmitter receptors within a defined cortical region. The practical validation we provide of the proposed tracking model reveals that it is a very promising approach, enabling accurate and fast processing of multiple images.