M. Birk, Alexander Guth, M. Zapf, M. Balzer, N. Ruiter, M. Hübner, J. Becker
{"title":"三维超声计算机断层扫描图像重建的加速:CPU、GPU和FPGA计算的评价","authors":"M. Birk, Alexander Guth, M. Zapf, M. Balzer, N. Ruiter, M. Hübner, J. Becker","doi":"10.1109/DASIP.2011.6136856","DOIUrl":null,"url":null,"abstract":"As today's standard screening methods frequently fail to diagnose breast cancer before metastases have developed, earlier breast cancer diagnosis is still a major challenge. Three-dimensional ultrasound computer tomography promises high-quality images of the breast, but is currently limited by a time-consuming synthetic aperture focusing technique based image reconstruction. In this work, we investigate the acceleration of the image reconstruction by a GPU, and by the FPGAs embedded in our custom data acquisition system. We compare the obtained performance results with a recent multi-core CPU and show that both platforms are able to accelerate processing. The GPU reaches the highest performance. Furthermore, we draw conclusions in terms of applicability of the accelerated reconstructions in future clinical application and highlight general principles for speed-up on GPUs and FPGAs.","PeriodicalId":199500,"journal":{"name":"Proceedings of the 2011 Conference on Design & Architectures for Signal & Image Processing (DASIP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Acceleration of image reconstruction in 3D ultrasound computer tomography: An evaluation of CPU, GPU and FPGA computing\",\"authors\":\"M. Birk, Alexander Guth, M. Zapf, M. Balzer, N. Ruiter, M. Hübner, J. Becker\",\"doi\":\"10.1109/DASIP.2011.6136856\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As today's standard screening methods frequently fail to diagnose breast cancer before metastases have developed, earlier breast cancer diagnosis is still a major challenge. Three-dimensional ultrasound computer tomography promises high-quality images of the breast, but is currently limited by a time-consuming synthetic aperture focusing technique based image reconstruction. In this work, we investigate the acceleration of the image reconstruction by a GPU, and by the FPGAs embedded in our custom data acquisition system. We compare the obtained performance results with a recent multi-core CPU and show that both platforms are able to accelerate processing. The GPU reaches the highest performance. Furthermore, we draw conclusions in terms of applicability of the accelerated reconstructions in future clinical application and highlight general principles for speed-up on GPUs and FPGAs.\",\"PeriodicalId\":199500,\"journal\":{\"name\":\"Proceedings of the 2011 Conference on Design & Architectures for Signal & Image Processing (DASIP)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2011 Conference on Design & Architectures for Signal & Image Processing (DASIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DASIP.2011.6136856\",\"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 2011 Conference on Design & Architectures for Signal & Image Processing (DASIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DASIP.2011.6136856","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Acceleration of image reconstruction in 3D ultrasound computer tomography: An evaluation of CPU, GPU and FPGA computing
As today's standard screening methods frequently fail to diagnose breast cancer before metastases have developed, earlier breast cancer diagnosis is still a major challenge. Three-dimensional ultrasound computer tomography promises high-quality images of the breast, but is currently limited by a time-consuming synthetic aperture focusing technique based image reconstruction. In this work, we investigate the acceleration of the image reconstruction by a GPU, and by the FPGAs embedded in our custom data acquisition system. We compare the obtained performance results with a recent multi-core CPU and show that both platforms are able to accelerate processing. The GPU reaches the highest performance. Furthermore, we draw conclusions in terms of applicability of the accelerated reconstructions in future clinical application and highlight general principles for speed-up on GPUs and FPGAs.