Advancing X-Ray Medical Imaging through Compton Scattering Technologies: A Systematic Review of Technological Developments and AI-Based Image Reconstruction
Abstract
Compton scattering has emerged as a promising advancement in X-ray medical imaging, offering enhanced spatial resolution and diagnostic precision compared to conventional techniques. This study employs a Systematic Literature Review (SLR) to evaluate the contributions of Compton scattering technologies in improving imaging performance. Forty peer-reviewed articles were selected from six major databases including Google Scholar, Scopus, PubMed, Web of Science, ScienceDirect, and arXiv based on predefined inclusion criteria. The review identifies three main technological approaches which are Compton cameras, inverse Compton X-ray sources, and Compton scattering tomography. Recent innovations in image reconstruction, particularly using deep learning and convolutional neural networks, have significantly improved image quality, reduced noise, and enhanced computational efficiency. These findings underscore Compton scattering’s clinical potential, especially in soft tissue visualization and early lesion detection. This paper provides a detailed overview of current progress and strategic pathways in the development of Compton based imaging systems towards their clinical application.
How strong is the evidence?
Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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