{"title":"使用DIC显微镜图像重建标本","authors":"F. Kagalwala, T. Kanade","doi":"10.1109/bibe.2000.889622","DOIUrl":null,"url":null,"abstract":"Differential Interference Contrast (DIC) microscopy is a powerful visualization tool used to study live biological cells. Its use, however, has been limited to qualitative observations. The inherent nonlinear relationship between the object properties and the image intensity makes quantitative analysis difficult. Towards quantitatively measuring optical properties of objects from DIC images, the authors develop a method to reconstruct the specimen's optical properties over a three-dimensional volume. The method is a nonlinear optimization which uses hierarchical representations of the specimen and data. As a necessary tool, the authors have developed and validated a computational model for the DIC image formation process. They test their algorithm by reconstructing the optical properties of known specimens.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Reconstructing specimens using DIC microscope images\",\"authors\":\"F. Kagalwala, T. Kanade\",\"doi\":\"10.1109/bibe.2000.889622\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Differential Interference Contrast (DIC) microscopy is a powerful visualization tool used to study live biological cells. Its use, however, has been limited to qualitative observations. The inherent nonlinear relationship between the object properties and the image intensity makes quantitative analysis difficult. Towards quantitatively measuring optical properties of objects from DIC images, the authors develop a method to reconstruct the specimen's optical properties over a three-dimensional volume. The method is a nonlinear optimization which uses hierarchical representations of the specimen and data. As a necessary tool, the authors have developed and validated a computational model for the DIC image formation process. They test their algorithm by reconstructing the optical properties of known specimens.\",\"PeriodicalId\":196846,\"journal\":{\"name\":\"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/bibe.2000.889622\",\"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 IEEE International Symposium on Bio-Informatics and Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/bibe.2000.889622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconstructing specimens using DIC microscope images
Differential Interference Contrast (DIC) microscopy is a powerful visualization tool used to study live biological cells. Its use, however, has been limited to qualitative observations. The inherent nonlinear relationship between the object properties and the image intensity makes quantitative analysis difficult. Towards quantitatively measuring optical properties of objects from DIC images, the authors develop a method to reconstruct the specimen's optical properties over a three-dimensional volume. The method is a nonlinear optimization which uses hierarchical representations of the specimen and data. As a necessary tool, the authors have developed and validated a computational model for the DIC image formation process. They test their algorithm by reconstructing the optical properties of known specimens.