{"title":"基于GPU的三维超声断层图像重建算法","authors":"Jiaduo Gong","doi":"10.1145/3596286.3596290","DOIUrl":null,"url":null,"abstract":"At present, X-ray technology, B-ultrasound and magnetic resonance imaging technology have more or less defects in the detection of female breast cancer, so the early detection of breast cancer is still a very important challenge. Ultrasound tomography (UT) can solve these problems very well. This project mainly uses the TVAL3 algorithm to reconstruct the original image from the information collected by the UT system for clinical use. TVAL3 algorithm involves a large number of matrix-vector multiplications and transposed matrix-vector multiplications, which will consume a lot of time if traditional CPU methods are used. For the characteristics of matrix-vector multiplication, this project uses CUDA to call GPU for parallel computing. At the same time, in order to further increase the speed of the calculation, we put part of the unchanged content into the GPU in advance to reduce the time spent on the transfer process. The final speedups of 20x, 10x and 5x were achieved in matrix vector multiplication, transpose matrix vector multiplication and total time, respectively.","PeriodicalId":208318,"journal":{"name":"Proceedings of the 2023 Asia Conference on Computer Vision, Image Processing and Pattern Recognition","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"3D Ultrasound Tomography Image Reconstruction Algorithm by GPU\",\"authors\":\"Jiaduo Gong\",\"doi\":\"10.1145/3596286.3596290\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, X-ray technology, B-ultrasound and magnetic resonance imaging technology have more or less defects in the detection of female breast cancer, so the early detection of breast cancer is still a very important challenge. Ultrasound tomography (UT) can solve these problems very well. This project mainly uses the TVAL3 algorithm to reconstruct the original image from the information collected by the UT system for clinical use. TVAL3 algorithm involves a large number of matrix-vector multiplications and transposed matrix-vector multiplications, which will consume a lot of time if traditional CPU methods are used. For the characteristics of matrix-vector multiplication, this project uses CUDA to call GPU for parallel computing. At the same time, in order to further increase the speed of the calculation, we put part of the unchanged content into the GPU in advance to reduce the time spent on the transfer process. The final speedups of 20x, 10x and 5x were achieved in matrix vector multiplication, transpose matrix vector multiplication and total time, respectively.\",\"PeriodicalId\":208318,\"journal\":{\"name\":\"Proceedings of the 2023 Asia Conference on Computer Vision, Image Processing and Pattern Recognition\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 Asia Conference on Computer Vision, Image Processing and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3596286.3596290\",\"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 2023 Asia Conference on Computer Vision, Image Processing and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3596286.3596290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
3D Ultrasound Tomography Image Reconstruction Algorithm by GPU
At present, X-ray technology, B-ultrasound and magnetic resonance imaging technology have more or less defects in the detection of female breast cancer, so the early detection of breast cancer is still a very important challenge. Ultrasound tomography (UT) can solve these problems very well. This project mainly uses the TVAL3 algorithm to reconstruct the original image from the information collected by the UT system for clinical use. TVAL3 algorithm involves a large number of matrix-vector multiplications and transposed matrix-vector multiplications, which will consume a lot of time if traditional CPU methods are used. For the characteristics of matrix-vector multiplication, this project uses CUDA to call GPU for parallel computing. At the same time, in order to further increase the speed of the calculation, we put part of the unchanged content into the GPU in advance to reduce the time spent on the transfer process. The final speedups of 20x, 10x and 5x were achieved in matrix vector multiplication, transpose matrix vector multiplication and total time, respectively.