RANSAC ART TOMOGRAPHY
Proceedings: GRAPHICON'2019 PROCEEDINGS. VOLUME 2
Authors:
1.
CMC MSU
Russian Federation
Russian Federation
2.
Institut prikladnoy matematiki im. M.V.Keldysha RAN
Russian Federation
Russian Federation
Type:
Сonference article
Published:
20.11.2019
Subject area:
GRNTI 20.01 Общие вопросы информатики
GRNTI 50.07 Теоретические основы вычислительной техники
BBK 3297 Вычислительная техника
GRNTI 50.07 Теоретические основы вычислительной техники
BBK 3297 Вычислительная техника
Language:
English
Keywords:
Tomography, Optical Tomography, ART, RANSAC, GPU
Abstract (English):
This paper describes using of per-voxel RANSAC approach in ART tomography. The method works as an addition to any ART and does not depend on its internal details. Firstly, the histograms of voxel map corrections are constructed in each voxel during usual pass of ART. Then, they are used to refine the absorption map. It allows to improve resulting voxel absorption map, reducing ghost effects caused by input data errors and inconsistency. This method was demonstrated with optical tomography algorithm as it has certain difficulties with input data. The proposed algorithm was implemented to run on GPU.
This paper describes using of per-voxel RANSAC approach in ART tomography. The method works as an addition to any ART and does not depend on its internal details. Firstly, the histograms of voxel map corrections are constructed in each voxel during usual pass of ART. Then, they are used to refine the absorption map. It allows to improve resulting voxel absorption map, reducing ghost effects caused by input data errors and inconsistency. This method was demonstrated with optical tomography algorithm as it has certain difficulties with input data. The proposed algorithm was implemented to run on GPU.
Keywords:
Tomography, Optical Tomography, ART, RANSAC, GPU
Tomography, Optical Tomography, ART, RANSAC, GPU
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