Fuzzy C-Means Based Automated Technique for Hippocampus Segmentation - Savita, Savita; Vijayalakshmi, S (International Journal of Computer Sciences and Engineering, 2025)
Evaluation of the Hippocampus structure is extremely important step regarding the precaution, detection as well as identification of numerous brain upheavals owing to the implication of the complex structural changes of the HC in those disorders. In this paper, a new hybrid method for segmenting the HC from MRI brain images is introduced by using clustering method Fuzzy C-Means which is very sensitive to noise. So prior to segmentation, pre-processing is done to make the image free of noise as well as with prominent Region of Interest. To segment HC, image features are computed to validate the slice to identify whether it comprises of Hippocampus or not. Enhancement techniques based on morphological operations and filters are applied to make a image clear. Finally FCM clustering method is used to get the HC from binary image. The result of the above said procedure ideally extracts the hippocampus. For Quantitative analysis of proposed method Dice and Jaccard parameters are used.