{"title":"使用GPGPU计算快速准确地确定体数据曲率","authors":"Jacob D. Hauenstein, Timothy S Newman","doi":"10.1145/3190645.3190681","DOIUrl":null,"url":null,"abstract":"A methodology for fast determination of a key shape feature in volume datasets using a GPU is described. The shape feature, surface curvature, which is a valuable descriptor for structure classification and dataset registration applications, can be time-consuming to determine reliably by conventional serial computing. The techniques here use parallel processing on a commodity GPU to achieve 100-fold (and above) improvements (for moderate-sized datasets) over conventional serial processing for curvature determination. Techniques for one class of curvature determination methods are detailed, including methods well-suited to datasets acquired by medical scanners.","PeriodicalId":403177,"journal":{"name":"Proceedings of the ACMSE 2018 Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast and accurate volume data curvature determination using GPGPU computation\",\"authors\":\"Jacob D. Hauenstein, Timothy S Newman\",\"doi\":\"10.1145/3190645.3190681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A methodology for fast determination of a key shape feature in volume datasets using a GPU is described. The shape feature, surface curvature, which is a valuable descriptor for structure classification and dataset registration applications, can be time-consuming to determine reliably by conventional serial computing. The techniques here use parallel processing on a commodity GPU to achieve 100-fold (and above) improvements (for moderate-sized datasets) over conventional serial processing for curvature determination. Techniques for one class of curvature determination methods are detailed, including methods well-suited to datasets acquired by medical scanners.\",\"PeriodicalId\":403177,\"journal\":{\"name\":\"Proceedings of the ACMSE 2018 Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACMSE 2018 Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3190645.3190681\",\"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 of the ACMSE 2018 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3190645.3190681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast and accurate volume data curvature determination using GPGPU computation
A methodology for fast determination of a key shape feature in volume datasets using a GPU is described. The shape feature, surface curvature, which is a valuable descriptor for structure classification and dataset registration applications, can be time-consuming to determine reliably by conventional serial computing. The techniques here use parallel processing on a commodity GPU to achieve 100-fold (and above) improvements (for moderate-sized datasets) over conventional serial processing for curvature determination. Techniques for one class of curvature determination methods are detailed, including methods well-suited to datasets acquired by medical scanners.