• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.117-126
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• 2008

Recent advances in medical imaging technologies have enabled the high-resolution data acquisition. Therefore visualization of such large data set on standard graphics hardware became a popular research theme. Among many visualization techniques, we focused on bricking method which divided the entire volume into smaller bricks and rendered them in order. Since it switches bet\W8n bricks on main memory and bricks on GPU memory on the fly, to achieve better performance, the number of these memory swapping conditions has to be minimized. And, because the original bricking algorithm was designed for regular volume data such as CT and MR, when applying the algorithm to ultrasound volume data which is based on the toroidal coordinate space, it revealed some performance degradation. In some areas near bricks' boundaries, an orthogonal viewing ray intersects the single brick twice, and it consequently makes a single brick memory to be uploaded onto GPU twice in a single frame. To avoid this redundancy, we divided the volume into bricks allowing overlapping between the bricks. In this paper, we suggest the formula to determine an appropriate size of these shared area between the bricks. Using our formula, we could minimize the memory bandwidth. and, at the same time, we could achieve better rendering performance.