M. G. González Ballester, Andrew Zisserman, M. Brady
{"title":"Combined statistical and geometrical 3D segmentation and measurement of brain structures","authors":"M. G. González Ballester, Andrew Zisserman, M. Brady","doi":"10.1109/BIA.1998.692379","DOIUrl":"https://doi.org/10.1109/BIA.1998.692379","url":null,"abstract":"Presents a novel method for three-dimensional segmentation and measurement of volumetric data based on the combination of statistical and geometrical information. The problem of shape representation of very complex three-dimensional structures, such as the brain cortex, is approached by combining the use of a discrete 3D mesh (the simplex mesh) with the construction of a smooth surface using triangular Gregory-Bezier patches. A Gaussian model for the tissues present in the image is adopted and a classification procedure which also estimates and corrects for the bias field present in the MRI is used. Confidence bounds are produced for all the measurements, thus obtaining a distribution on the position of the surface segmenting the image as the output of the method. Performance is tested both on real data and simulations of MR volumes, which provide ground truth. The method is also compared with other existing techniques.","PeriodicalId":261632,"journal":{"name":"Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130406486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The space-time map applied to Drosophila embryogenesis","authors":"P. Janardhan, M. Hebert, K. Ikeuchi","doi":"10.1109/BIA.1998.692429","DOIUrl":"https://doi.org/10.1109/BIA.1998.692429","url":null,"abstract":"Many physical phenomena have complex structure in both space and time. To systematically understand these phenomena from images one needs representations that unify the treatment of space and time. The authors create such a representation, the space-time map, for characterizing contour evolutions. Many types of information are computed and stored as facets of the map, registered to a space-time manifold generated by the evolution. The authors demonstrate their representation on the example of Drosophila embryogenesis in optical section. Changes in embryo shape are reflected as changes in the dye distribution along the deforming vitelline membrane contour. The authors extract a series of contours and create a two-dimensional space-time map. They track intensity on this map to obtain a velocity field. They extract space-time ridges and significant motions on this map, and use them along with prior knowledge to recognize the significant features and events of embryogenesis.","PeriodicalId":261632,"journal":{"name":"Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130964891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}