Comparative Review of Image Denoising and Segmentation Approaches For Detection of Tumor in Brain Images

Abstract

A group of defective cells that grow inside or around the brain referred as Barin Tumor. The number of Brain Tumor cases around the World is increasing day by day. So, it is significant to detect it at anearly stage. Segmentation of brain images holds thesignificant part for detection of Tumor brain. Manual segmentation of brain Tumor tissues cannot be compared with existing high-speed computing machines. Therefore, theemphasisis given on computer aided detection of brain Tumor. This paper provides an overview of various techniques that have been implemented till now to detect the brain tumor. Along with this, these techniques are compared for accuracy, sensitivity, and specificity to detect the Brain tumor. The research findings will help to explore the research in the same field.

Memory Organization for Image Segmentation Based on Region Growing

“…For avoiding limitation of memory resources, researchers developing an methods of image compression [5], while it's possible to reduce required memory by image pre-processing techniques. Among image pre-processing algorithms, segmentation algorithms are the most demanding of RAM capacity [6][7][8][9]. Segmentation result leads to the separation of an image into areas with the same or similar properties.…”