Exploring DL Methodologies for Medical Imaging: A Comprehensive Study

In the field of Medical Image Analysis information stays extracted from medical Image including MRIs, CT scans and X-rays, utilizing computational technique. This paper's objective is to provide an extensive overview of DL approaches for biomedical analysis of images. It covers multiple technologies established in analysis of medical images using DL approaches applicable for multiple recognition of patterns tasks. This recognition of pattern problems includes detection, segmentation, registration and classification. It gives a summary of the Several deep learning deep learning methodologies, inclusive of CNN, RNN, GAN, SNN, DBN, GNN, DCNN. This evaluates the application of deep learning to tasks such image categorization, the process of segmentation and identifying objects and registration. Brief summaries of research are given for each application are such as liver, lungs, brain are discussed in tables. This survey incorporates most important DL techniques and gives a complete guide from the recent works with method, application, results, merits and demerits of the analysis of medical images.