Medical data such as CT, MRI, PET etc are often stored in the DICOM format has great role in the treatment and diagnosis field. The vital part of medical image processing is the segmentation. Researchers have been dedicated to study the medical images and extract meaningful data such as shape, volume, texture and anomalies which will aid diagnosis and detection of disease such lesion, tumour and cancer. Image delineation plays a good role in this. This paper analyses the state-of-the-art medical image segmentation approaches, advantages and disadvantages. The classification of segmentation types found in this paper are not at all rigid but are made to suit explanatory convenience.
Volume 11 | 09-Special Issue
Pages: 612-622
DOI: 10.5373/JARDCS/V11/20192613