Advancements in Medical Imaging

Abstract

Medical imaging holds a pivotal role in modern healthcare, facilitating early disease identification, treatment planning, and patient progress monitoring. The integration of machine learning (ML) has significantly transformed medical imaging, offering automated analysis, pattern recognition, and diagnostic support. However, a notable paradigm shift has emerged in recent times, highlighting the ascendancy of deep learning (DL) techniques, heralding a new era in this field. This exploration scrutinizes the dynamic evolution within medical imaging, accentuating the departure from conventional machine learning methods toward the more advanced domain of deep learning. It scrutinizes the foundational principles of machine learning as applied in medical imaging, shedding light on the constraints that prompted the adoption of deep learning methodologies. Furthermore, the chapter explores the efficacy of deep learning models across diverse medical imaging modalities encompassing MRI, CT scans, X-rays, and ultrasound.