survey on automated medical image classification using deep learning

Abstract

Deep Learning has indeed been widely used in many fields/areas of medicinal images classification, and a large number of publications have been published documenting its success. The key for achieving effective diagnosis and therapy is accurate characterization of medical pictures. However, because image interpretation is highly dependent on the subjective opinion of doctors, the results of image processing vary greatly amongst clinicians at different levels. Picture classification, target identification, and image analysis have all improved dramatically in recent years with environmental image data sets in domain of Image Processing. In this paper, we have presented a systematic survey on feature extracting and classifying the medical images using deep learning methods. Two new ideas are presented in this work. First and foremost, we classified presently trendy publications in a multi-level configuration. Second, this research article concentrates on supervised and poorly supervised learning techniques.