Medical image segmentation: hard and soft computing approaches

Prajawal Sinha, Mayur Tuteja, Sanjay Saxena
2020 SN Applied Sciences  
Segmentation divides an image into discrete provinces containing pieces of pixels with analogous attributes. To be expressive and useful for image analysis and interpretation, the regions should strongly relate to depicted objects or features of interest. Different soft computing and hard computing methods are used for medical image segmentation for efficient accuracy. These are computing methods where hard computing is the conventional methodology, which relies on the principles of accuracy,
more » ... rtainty, and inflexibility. Conversely, soft computing is a modern approach premised on the idea of the approximation, uncertainty, and flexibility. Accurate segmentation is very necessary for medical images for better treatment planning. This article provides an efficient analysis of medical images using hard and soft computing. Further, it will explain data used, results obtained, and observation of the current literatures available for medical image segmentation.
doi:10.1007/s42452-020-1956-4 fatcat:qosggz567vgi3jyuuhmlwdtedu