{"title":"加速体绘制和层析重建使用纹理映射硬件","authors":"B. Cabral, N. Cam, Jim Foran","doi":"10.1145/197938.197972","DOIUrl":null,"url":null,"abstract":"Volume rendering and reconstruction centers around solving two related integral equations: a volume rendering integral (a generalized Radon transform) and a filtered back projection integral (the inverse Radon transform). Both of these equations are of the same mathematical form and can be dimensionally decomposed and approximated using Riemann sums over a series of resampled images. When viewed as a form of texture mapping and frame buffer accumulation, enormous hardware enabled performance acceleration is possible.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1084","resultStr":"{\"title\":\"Accelerated volume rendering and tomographic reconstruction using texture mapping hardware\",\"authors\":\"B. Cabral, N. Cam, Jim Foran\",\"doi\":\"10.1145/197938.197972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Volume rendering and reconstruction centers around solving two related integral equations: a volume rendering integral (a generalized Radon transform) and a filtered back projection integral (the inverse Radon transform). Both of these equations are of the same mathematical form and can be dimensionally decomposed and approximated using Riemann sums over a series of resampled images. When viewed as a form of texture mapping and frame buffer accumulation, enormous hardware enabled performance acceleration is possible.\",\"PeriodicalId\":124559,\"journal\":{\"name\":\"Symposium on Volume Visualization\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1084\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Symposium on Volume Visualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/197938.197972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Symposium on Volume Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/197938.197972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Accelerated volume rendering and tomographic reconstruction using texture mapping hardware
Volume rendering and reconstruction centers around solving two related integral equations: a volume rendering integral (a generalized Radon transform) and a filtered back projection integral (the inverse Radon transform). Both of these equations are of the same mathematical form and can be dimensionally decomposed and approximated using Riemann sums over a series of resampled images. When viewed as a form of texture mapping and frame buffer accumulation, enormous hardware enabled performance acceleration is possible.