HIGH-PERFORMANCE ANALYSIS METHOD AND MORPHOLOGICAL IMAGE PROCESSING
Segmentation is a difficult stage in the processing and analysis of medical images. This is due to the high variability of their characteristics, low contrast processed images and the organization of complex geometric objects. The article covers the realization of Sobel operator and Canny algorithm using OpenMP parallel programming technology and NVIDIA CUDA. It is shown that the implementation of these algorithms for GPUs with CUDA technology improves imaging performance. Completion of the computational experiment showed the effectiveness of the implementation of Canny algorithm using CUDA technology, compared with OpenMP for different resolutions of medical images.
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