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International Journal of Medical Toxicology & Legal Medicine
Year : 2023, Volume : 26, Issue : 3and4
First page : ( 42) Last page : ( 48)
Print ISSN : 0972-0448. Online ISSN : 0974-4614.
Article DOI : 10.5958/0974-4614.2023.00043.8

Role of Artificial Intelligence in Forensic Radiology

Verma Ankush1,*, Chouhan Amit Pratap Singh2, Singh Vandana3

1Department of Radiology, Sharda School of Allied Health Sciences, Sharda University, Greater Noida, 201310, India

2Department of Radiology, Sharda School of Allied Health Sciences, Sharda University, Greater Noida, 201310, India

3Department of Microbiology, Sharda School of Allied Health Sciences, Sharda University, Greater Noida, 201310, India

*Corresponding Author, Mr. Ankush Verma, Department of Radiology, Sharda School of Allied Health Sciences, Sharda University, Greater Noida, 201310, India, Phone: e-mail: ankushverma.anku@gmail.com, ankush.verma@sharda.ac.in

Online Published on 12 January, 2024.

Abstract

Forensic radiology is the use of imaging techniques, such as X-rays and CT scans, in legal investigations and court proceedings. Artificial intelligence (AI) can play a significant role in forensic radiology by helping to analyze and interpret imaging data. AI algorithms can be used to automatically detect and classify injuries, identify patterns and anomalies, and assist with image analysis and interpretation. This can help to improve the accuracy and efficiency of forensic radiology, and aid in the identification and prosecution of criminals. Additionally, AI can also be used to aid in the detection of certain types of injuries that are difficult to diagnose using traditional methods, such as child abuse or elder abuse. One specific application of AI in forensic radiology is the use of computer-aided detection (CAD) systems. These systems use machine learning algorithms to automatically identify and highlight suspicious areas in imaging studies, such as fractures or other types of injuries. This can help radiologists to more quickly and accurately identify injuries, and can also assist with the interpretation of imaging studies in cases where the radiologist may be less familiar with the specific injury or condition. This can help to improve the accuracy and consistency of injury classification, and can also aid in the identification of injuries that may be difficult to detect using traditional methods. AI can also help radiologist to analyze and compare large amounts of imaging data quickly. This can be useful in forensic radiology, where multiple imaging studies may need to be analyzed in order to identify injuries and determine the sequence of events. However, the use of AI in forensic radiology holds great promise for improving the accuracy and efficiency of legal investigations and court proceedings, and for helping to identify and prosecute criminals.

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Keywords

Artificial Intelligence, Radiology, Forensic, Computer-aided detection, Computed Tomography, Magnetic Resonance Imaging.

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