L. Long, Sameer Kiran Antani, J. Jeronimo, M. Schiffman, M. Bopf, Leif Neve, Carl Cornwell, S. Budihas, G. Thoma
{"title":"利用大量子宫颈图像中的生物标志物进行医学教育、研究和疾病筛查的技术","authors":"L. Long, Sameer Kiran Antani, J. Jeronimo, M. Schiffman, M. Bopf, Leif Neve, Carl Cornwell, S. Budihas, G. Thoma","doi":"10.1109/CBMS.2006.154","DOIUrl":null,"url":null,"abstract":"The Communications Engineering Branch of the National Library of Medicine is collaborating with the National Cancer Institute (NCI) in developing applications for medical education, research, and disease screening for precancer detection in the uterine cervix. These applications include (1) expert marking/labeling of tissue regions, (2) Web viewing/interpretation of histology images, (3) image database/retrieval, and (4) training/testing in clinical image interpretation. Initial NCI studies have been conducted in expert cervicography marking and histology evaluation. We are working toward making cervix images searchable by content-based image retrieval (CBIR). Image pre-processing to remove specular reflection artifacts has achieved 90% success (120 images). Similar results have been obtained for automated location of cervix regions, using Gaussian mixture modeling (GMM) with Lab color and one geometric feature. We describe initial classification experiments to discriminate clinically significant tissue, using RGB, HSV, Lab, and YCbCr color models, texture measures, and GMM, fuzzy C-means, and deterministic annealing algorithms","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Technology for Medical Education, Research, and Disease Screening by Exploitation of Biomarkers in a Large Collection of Uterine Cervix Images\",\"authors\":\"L. Long, Sameer Kiran Antani, J. Jeronimo, M. Schiffman, M. Bopf, Leif Neve, Carl Cornwell, S. Budihas, G. Thoma\",\"doi\":\"10.1109/CBMS.2006.154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Communications Engineering Branch of the National Library of Medicine is collaborating with the National Cancer Institute (NCI) in developing applications for medical education, research, and disease screening for precancer detection in the uterine cervix. These applications include (1) expert marking/labeling of tissue regions, (2) Web viewing/interpretation of histology images, (3) image database/retrieval, and (4) training/testing in clinical image interpretation. Initial NCI studies have been conducted in expert cervicography marking and histology evaluation. We are working toward making cervix images searchable by content-based image retrieval (CBIR). Image pre-processing to remove specular reflection artifacts has achieved 90% success (120 images). Similar results have been obtained for automated location of cervix regions, using Gaussian mixture modeling (GMM) with Lab color and one geometric feature. We describe initial classification experiments to discriminate clinically significant tissue, using RGB, HSV, Lab, and YCbCr color models, texture measures, and GMM, fuzzy C-means, and deterministic annealing algorithms\",\"PeriodicalId\":208693,\"journal\":{\"name\":\"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.2006.154\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2006.154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Technology for Medical Education, Research, and Disease Screening by Exploitation of Biomarkers in a Large Collection of Uterine Cervix Images
The Communications Engineering Branch of the National Library of Medicine is collaborating with the National Cancer Institute (NCI) in developing applications for medical education, research, and disease screening for precancer detection in the uterine cervix. These applications include (1) expert marking/labeling of tissue regions, (2) Web viewing/interpretation of histology images, (3) image database/retrieval, and (4) training/testing in clinical image interpretation. Initial NCI studies have been conducted in expert cervicography marking and histology evaluation. We are working toward making cervix images searchable by content-based image retrieval (CBIR). Image pre-processing to remove specular reflection artifacts has achieved 90% success (120 images). Similar results have been obtained for automated location of cervix regions, using Gaussian mixture modeling (GMM) with Lab color and one geometric feature. We describe initial classification experiments to discriminate clinically significant tissue, using RGB, HSV, Lab, and YCbCr color models, texture measures, and GMM, fuzzy C-means, and deterministic annealing algorithms