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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Junqing Shang Managuli, R. Yongmin Kim |
| Copyright Year | 2009 |
| Description | Author affiliation: Departments of Bioengineering and Electrical Engineering, University of Washington, Seattle, 98195 USA (Junqing Shang; Managuli, R.; Yongmin Kim) |
| Abstract | Arbitrary volume reslicing (AVR) is used to generate 2D planes of any orientation from 3D data. Pre-scan-converted (pre-SC) AVR avoids the 3D scan conversion (SC) step and directly uses a pre-SC volume to generate 2D AVR planes. AVR is typically performed on a PC system external to the ultrasound frontend and backend. In this paper, we present an efficient pre-SC AVR algorithm in an ultrasound backend system. The backend supports AVR natively with other backend functions, so the PC system does not need to compute 2D AVR planes from 3D volumes. We used phantom and in vivo datasets to evaluate the pre-SC and post-SC AVR. The normalized root mean squared difference (NRMSD) was 1.23% for phantom data, and 1.21% for in vivo data. Using one of 8 cores in a multi-core processor, Cell, our algorithm can generate a 1024×768 16-bit AVR image in 30.2 ms from a 512×136×64 16-bit input volume. |
| Starting Page | 2320 |
| Ending Page | 2323 |
| File Size | 1403979 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424443895 |
| ISSN | 19485727 |
| DOI | 10.1109/ULTSYM.2009.5441615 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-20 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ultrasonic imaging Signal processing algorithms Biomedical imaging Imaging phantoms In vivo Multicore processing Color Data visualization Field programmable gate arrays Engineering management Cell processor 3D ultrasound arbitrary volume reslicing multi-core processor volume rendering ultrasound backend |
| Content Type | Text |
| Resource Type | Article |
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