Laser & Optoelectronics Progress, Volume. 55, Issue 5, 051701(2018)
Research and Realization of Local Cardiovascular Computed Tomography Extraction Algorithm in Lesion Assisted Diagnosis
To extract four-dimensional computed tomography (CT) images of lesion blood vessels with real-time interaction in imaging examination, we propose a parallel region growing algorithm with optimized mind evolutionary algorithm (MEA). The parallel region growing algorithm with optimized MEA based on the three-level thread processing queue can avoid local optimum through self-evolution, and can improve convergence speed and blood vessel segmentation accuracy. Any part of the interactive cardiac lesion vascular extraction and four-dimensional visualization can be achieved with the aids of the visualization toolkit (VTK) and computer graphics library. The results show that extraction time and volume rendering velocity with ten phases of local blood vessels of interest are significantly improved, and frames per second (FPS) of local blood vessel extraction can reach about 30. If interactive manipulations such as rotation, shrinkage, and enlargement appear in the display process, the FPS will decrease to about 21, but the real-time display of cardiovascular can be obtained successfully. The local cardiovascular regional extraction technique can assist doctors to observe the lesion area of cardiovascular disease, and provide an intuitive and effective visual basis for the diagnosis of cardiovascular disease.
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Guoyin Ren, Xiaoqi Lü, Nan Yang, Dahua Yu. Research and Realization of Local Cardiovascular Computed Tomography Extraction Algorithm in Lesion Assisted Diagnosis[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051701
Category: Medical optics and biotechnology
Received: Sep. 22, 2017
Accepted: --
Published Online: Sep. 11, 2018
The Author Email: Ren Guoyin (renguoyin@imust.edu.cn)