{"title":"小鼠脑细胞的三维边界重建","authors":"Y. Guan, M. Opas, Y. T. Lee, Y. Cai","doi":"10.1109/ICARCV.2006.345482","DOIUrl":null,"url":null,"abstract":"This paper reports our 3D reconstruction work of mouse brain cells from a confocal image stack. Gradients at volumetric points are used for boundary surface extraction and structure visualization from 3D volumetric confocal microscopic images. We present a method to automatically evaluate the suitability of gradients for 3D boundary identification. The approach developed is applied for 3D reconstruction of mouse brain cells from confocal image stack","PeriodicalId":415827,"journal":{"name":"2006 9th International Conference on Control, Automation, Robotics and Vision","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"3D Boundary Reconstruction of Mouse Brain Cells\",\"authors\":\"Y. Guan, M. Opas, Y. T. Lee, Y. Cai\",\"doi\":\"10.1109/ICARCV.2006.345482\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper reports our 3D reconstruction work of mouse brain cells from a confocal image stack. Gradients at volumetric points are used for boundary surface extraction and structure visualization from 3D volumetric confocal microscopic images. We present a method to automatically evaluate the suitability of gradients for 3D boundary identification. The approach developed is applied for 3D reconstruction of mouse brain cells from confocal image stack\",\"PeriodicalId\":415827,\"journal\":{\"name\":\"2006 9th International Conference on Control, Automation, Robotics and Vision\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 9th International Conference on Control, Automation, Robotics and Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICARCV.2006.345482\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 9th International Conference on Control, Automation, Robotics and Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2006.345482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper reports our 3D reconstruction work of mouse brain cells from a confocal image stack. Gradients at volumetric points are used for boundary surface extraction and structure visualization from 3D volumetric confocal microscopic images. We present a method to automatically evaluate the suitability of gradients for 3D boundary identification. The approach developed is applied for 3D reconstruction of mouse brain cells from confocal image stack
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