Comparison of GPU-based and CPU-based algorithms for determining the minimum distance between a CUSA scalpel and blood vessels

Noborio, Hiroshi; Kunii, Takahiro; Mizushino, Kiminori

doi:10.5759/jscas.16.13

Cited by 1 publication

(5 citation statements)

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“…A year ago, we first proposed the one-directional shortest Euclidean distance calculation algorithm [9]. We developed this GPU-based algorithm for calculating the distance and/or intersection detection between a point and an object or multiple objects to solve a significant problem with the classic CPU-based algorithm.…”

Section: Methodsmentioning

confidence: 99%

“…3 presents the application of the one-directional algorithm in an arbitrary surgical simulation and/or navigation in the 2D environment. This 3D version was tested in a virtual environment, including the CUSA and blood vessel STL [9]. We used a sequence of bits that corresponded to each digitized distance.…”

Section: Methodsmentioning

confidence: 99%

“…First, the following procedure is simultaneously used for all (one in [9]) the rectangular parallelepipeds within the six digitized cubes around the CUSA tip along the X, -X, Y, -Y, Z and -Z axes:…”

Section: International Journal Of Bioscience Biochemistry and Bioinfmentioning

confidence: 99%

“…As a result, a cuboid can be obtained with the width and pixilation calculated using the z-value of the surface and the reverse side of the polyhedron, resulting in a cuboid digital approximation of the polyhedra. Therefore, we can calculate the Euclidean distances from the tip of the scalpel to the rectangular parallelepipeds in parallel using multi-cores of the GPU, the smallest of which represents the shortest distance for one arbitrary direction [9].…”

Section: Introductionmentioning

confidence: 99%

“…On the basis of the above mentioned pre-processing, we calculated the shortest distance from the CUSA tip to the three types of blood vessels (portal veins, arteries, and veins) along the CUSA's moving direction, having a single dimension [9]. In this omni-directional algorithm, the previously revised algorithm calculates the shorter Euclidean distances six times individually around the CUSA tip along the X, -X, Y, -Y, Z and -Z axes and then selects the shortest distance from the six shorter ones [13].…”

Section: Introductionmentioning

confidence: 99%

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Omni-Directional Shortest Distance Algorithm by Complete Parallel-Processing Based on GPU Cores

Noborio¹,

Kunii²,

Mizushino³

2018

IJBBB

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Abstract:We propose a new algorithm for calculating the 3D omni-directional minimum distance from the cavitron ultrasonic surgical aspirator (CUSA) tip to blood vessels. The distance is selected from many shorter distances calculated by the GPU cores for many pixels. First, we use z-buffering (depth buffering) as the classic matured function of the GPU to effectively obtain depths (the distances to blood vessels) corresponding to many pixels. Second, we calculate the Euclidean distance from the scalpel tip to the closest z-values of the depths by multiple GPU cores for all pixels. The many pixels are prepared within a cubic region overlapped by six rectangular parallelepipeds along the +X, -X, +Y, -Y, +Z, and -Z axes centered at the CUSA tip. In this algorithm, all cores are not distinguished within six cubes. Finally, we evaluate the algorithm performance with regard to calculation time and visual reality using an inexpensive GPU (GTX950). Our experimental results show that the calculation time is twice as fast, and the visual reality is also improved.Key words: CUSA (cavitron ultrasonic surgical aspirator), DICOM (digital imaging and communication in medicine), GPGPU (general-purpose graphics processing unit), STL (STereo-lithographies), Z-buffering (depth buffering).

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: International Journal Of Bioscience Biochemistry and Bioinfmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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