Computed Tomography Image Reconstruction for Disease Prediction: A Systematic Review

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Abstract

A common medical imaging method that produces clear images of the internal body structures is computed tomography (CT). Recent advancements in CT technology have enabled the development of sophisticated image reconstruction techniques that can enhance image quality and aid in disease diagnosis and prediction. In this systematic review, we summarize the present state of research on CT image reconstruction for disease prediction. We searched PubMed, Embase, and Scopus databases for studies published between 2010 and 2022 that used CT image reconstruction for disease prediction. After screening and eligibility assessment, we included 48 studies in the review. The studies were categorized into four groups based on the disease area of focus: cardiovascular disease, respiratory disease, cancer, and neurological disease. The study demonstrated the effectiveness of CT image reconstruction for disease prediction in various disease areas.

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Keywords

Computed tomography; Artificial intelligence; Machine learning.