Evolution in Spinal Fracture Diagnosis and Brain Tumor Detection in the Last two Decades: A Timeline-Based Study

Abstract

Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are arguably the most prominent and most widely used healthcare diagnostic modalities for a wide range of applications. There are certain specific applications for which a particular modality is specifically used or has been adopted over a period of time because of reasons like good diagnostic accuracy, fast diagnosis, etc. One such application for CT has been “Spinal Fracture Diagnosis” and for MRI has been “Brain Tumor Detection”. This study presents case studies from different time periods to demonstrate the evolution of these respective applications and emphasizes the role of Artificial Intelligence (AI) based techniques like machine learning, deep learning, etc. for advancements in the diagnostic process. The case studies will enable the new researchers to understand the background and the work done in the respective time period. The time period of the studies referred to is between the years 2000 and 2023 (Present date). The purpose of this study is to enlighten the reader about the evolution of spinal fractures and brain tumor diagnosis which are understood to be primary applications of CT and MRI, respectively and, encourage further study into topics pertaining to AI-based tools used in diagnostic modalities for applications like automatic detection and prediction, smart decision making, early detection, etc.