High Performance Computation Analysis for Medical Images using High Computational Methods
Ashwini Shewale, Nayan Waghmare, Anuja Sonawane, Utkarsha Teke · 2016
Medical image processing can be done through various methods, but it may take long time for processing it. As the processing time is increased it delays the report generation which can affect patient's life. So to scale down the medical image processing time and without getting arousing effect on the quality of image, High computational medical image processing methods are being used. Here in the proposed system, to deal with the medical image different theorems are used (Image registration, Image Segmentation, Image de-noising). Image registration regulates the image, the image is then segmented into identical structures using Image Segmentation. The image may have different types of noise in it. So, to expel this noise Image De-noising will be used. As the processing will be done in individual environments (CPU and GPU), the efficiency in both the situations will be analyzed. Reasonably, GPU will be the capable environment for medical image processing. This proposed system can be used to process different techniques like MRI, CTScan, etc.