ML-based Medical Image Analysis for Anomaly Detection in CT Scans, X-rays, and MRIs

Abstract

The area of medical image analysis is examined in this review article along with its potential to revolutionize healthcare. The article starts off by going through the different kinds of medical imaging, such as CT scans, X-rays, and MRIs, as well as the difficulties in analyzing these images. The discussion then switches to the use of machine learning algorithms to identify anomalies in medical pictures, emphasising the value of high-quality data and inter professional cooperation. The study also discusses the difficulties in analyzing medical images, including the need for more reliable machine learning algorithms and standardized techniques for image acquisition. The significance of creating clear norms and laws is also emphasized, along with concerns about patient privacy and data security. A discussion of recent developments and potential future paths in medical image analysis is included in the article's conclusion. Personalised medicine, the utilization of augmented reality and virtual reality technology, and the creation of visible and comprehensible machine learning algorithms are a few of these. The essay gives a thorough summary of the state of medical image analysis now and how it could revolutionize healthcare as a whole.