Integration of segmentation techniques to detect cyst in human brain using MRI sequences

The main objective of this paper is to present an analytical method to detect lesions (cysts) in digitized MRI data. Segmentation techniques are applied on different sequences of MRI images (T1&T2) which helps to differentiate between malignant region from normal region in the given original image. The abnormal part is captured in the JPEG format. The segmentation of the image is then used to detect the part of the image which depicts abnormalities more accurately. The proposed algorithm helps the radiologists to take primitive measures for diagnosis. An efficient method by integrating thresholding and canny edge detector has been explained in this paper. This process requires very less time and hence the method can detect the cyst in the early stage more accurately. Time complexity of the advanced segmentations is also discussed in this paper.