An Automated Enhanced FCM Based Hippocampus Segmentation

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S. Vijayalakshmi, Savita


Fragmentation of image in digital image processing is a major issue in medical field. One of the unique characteristic of image is the interaction between adjacent pixels. To extract semantic relationship between the pixels segmentation is used. Lots of algorithms have been developed for segmentation. In recent years, human hippocampus has received the focus of research because of its close link with memory and neurological disorders. To identify and to diagnose neurological disorders, hippocampus is to be segmented. But its small size and complex structure make the segmentation process a very tedious task. In this paper an enhanced Fuzzy C-Means (FCM) method is present to extract hippocampus from human brain MRI. In this proposed method, segmentation of hippocampus is done in two stages: Stage1 involves validation and preprocessing whereas stage2 comprises of segmentation using FCM. To validate and confirm the performance of the presented method with previously available tool and for the comparison between proposed and manual segmented methods Jaccard (j) and dice (d) are calculated.

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S. Vijayalakshmi, Savita. (2021). An Automated Enhanced FCM Based Hippocampus Segmentation. Annals of the Romanian Society for Cell Biology, 1861–1871. Retrieved from