2010
DOI: 10.1109/icbbe.2010.5516870
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Fast GPU-Based Automatic Time Gain Compensation for Ultrasound Imaging

Abstract: The Compute Unified Device Architecture (CUDA) is a new programming platform making use of the unified shader design of the most current Graphics Processing Units (GPUs) from NVIDIA. In this paper, we apply this revolutionary new technology to implement the automatic time gain compensation (ATGC) for medical ultrasound imaging. The parallel box filtering method and general matrix computation algorithms are also presented. This ATGC method achieves a frame rate of 125 fps for the 512×261 image, about 79 times f… Show more

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Cited by 4 publications
(4 citation statements)
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“…Gain compensation adjusts the intensity of the mosaic by computing the local mean brightness of the image. Nevertheless, simply adjusting the gain to give all regions the same medium intensity will tend to reduce the intensity in regions with high brightness and increase the dark or low-intensity regions [56]. Multiband image blending is proposed in [57], and it is one of the most popular applications for image fusion due to its easy implementation and its advantage of being insensitive to misalignment.…”
Section: Introductionmentioning
confidence: 99%
“…Gain compensation adjusts the intensity of the mosaic by computing the local mean brightness of the image. Nevertheless, simply adjusting the gain to give all regions the same medium intensity will tend to reduce the intensity in regions with high brightness and increase the dark or low-intensity regions [56]. Multiband image blending is proposed in [57], and it is one of the most popular applications for image fusion due to its easy implementation and its advantage of being insensitive to misalignment.…”
Section: Introductionmentioning
confidence: 99%
“…From [7], we can see coarse-grained parallel way for box filter is better than the fine-grained way. The coarse-grained parallel way defined as each thread processing a whole row and column.…”
Section: ) Post-processing (Kernel 5 To 21)mentioning
confidence: 91%
“…From [6], we know that coarse-grained parallel way defined as each thread processing a whole row and column has better performance than the fine-grained one. However, the x (row) pass suffers from un-coalesced global memory reads, because each thread is reading from different rows.…”
Section: ) Speckle Detection (Kernel 1~2)mentioning
confidence: 99%