Image Processing Tasks using Parallel Computing in Multi core Architecture and its Applications in Medical Imaging

To find accurate & reliable result in image analysis, it is important that image is processed and analyzed using image processing suitable AI technique further at the same time it is highly desired that processing time must be minimum. Preprocessing of the image makes it more clear and visible, while parallelizing of the algorithm optimizes the speed at which the image is processed. This paper explores current multi-core architectures available in commercial processors in order to speed up the image processing tasks. Parallel Implementation of Many sequential algorithms of Image processing was examined and analyzed in test and achieved good result if all the recourses are efficiently used. Main objective of this paper is to design some parallel image processing algorithms like segmentation, noise reduction, features calculation, histogram equalization etc by using Multi Core architecture and comparative study with some sequential image processing algorithm. These parallel algorithms are able to work with different number of thread, so as to take all the benefits of the upcoming processors having any number of cores. As medical imaging refers to view the human body in order to diagnose, monitor and treatment planning. This paper also describes the application of parallel computing applied in different Medical Imaging techniques like CT, PET scans etc.