Self-Learning Network-based segmentation for real-time brain M.R. images through HARIS.

ABSTRACT: In recent years in medical imaging technology, the advancement for medical diagnosis, the initial assessment of the ailment, and the abnormality have become challenging for radiologists. Magnetic resonance imaging is one such predominant technology used extensively for the initial evaluation of ailments. The primary goal is to mechanizean approach that can accurately assess the damaged region of the human brain throughan automated segmentation process that requires minimal training and can learn by itself from the previous experimental outcomes. It is computationally more efficient than other supervised learning strategies such as CNN deep learning models. As a result, the process of investigation and statistical analysis of the abnormality would be made much more comfortable and convenien

SUBMITTER: Naga Srinivasu P 

PROVIDER: S-EPMC8356652 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature