Paper Details

Recent research has placed a premium on medical image processing. Medical image processing is a discipline that has evolved from an active and fast expanding field. Medical image segmentation is an important step in medical studies for diagnosis (X-ray, CT, MRI, PET), controlling, and surgical planning. Physically segmenting medical images is a time consuming and labor-intensive process. As a result, high-accuracy automated segmentation algorithms are appealing. A segmentation algorithm's performance is determined by a number of critical factors like accuracy of the results, the segmentation technique's application area and so on.[1]Fuzzy C means clustering, as one type of image segmentation technique, is an effective and compact segmentation approach. Fuzzy c-means (FCM) clustering is the most precise method for image segmentation in unsupervised methods, and it can be smooth and produce intended outcomes. This paper discusses medical picture modalities and mathematically explains the processes of the FCM clustering algorithm with output. It partitions the disc which is present in between the vertebral on magnetic resonance imaging (MRI) of the spine, using the FCM segmentation method; we were able to achieve a decent result of up to 70.41 percent average accuracy on total 80 MRI spine images

Spine MRI image, Medical Image Modality, Segmentation, Fuzzy C-means clustering( FCM), Morphological filtering.