Correlating the Machine Learning Models for Automatic Error Detection and Correction in Medical Images

摘要

Medical image has always been considered as a significant research area when it comes to advanced analysis in the critical disease diagnosis process. There has been massive archival of research works based on the medical image concerning the classification and analysis. In this regard, this paper has identified two core techniques that have been frequently used over images viz. i) optical character recognition and ii) machine learning. Both the system has its own benefits and limitation as witnessed in many research works. The contribution of this paper is to find out an essential correlation between these two frequently used models over images so that a novel form of solution can be developed in future applications based on medical images. This paper briefs all the essential information available on the existing approaches of both the system focusing mainly on both the error correction methods and learning methods. It is anticipated that the finding of this paper will assist in deploying a better decision to choose machine learning and it's applicability shortly.