Automatic Medical Report Generation: Methods and Applications
It addresses the bottleneck of radiologist shortages in healthcare, but as a review, it is incremental in synthesizing existing literature rather than presenting new findings.
This review paper tackles the problem of diagnostic delays and misdiagnoses in medical imaging by examining automatic medical report generation (AMRG) methods from 2021 to 2024, providing a comprehensive overview of solutions, applications, datasets, and evaluation metrics to inspire future research.
The increasing demand for medical imaging has surpassed the capacity of available radiologists, leading to diagnostic delays and potential misdiagnoses. Artificial intelligence (AI) techniques, particularly in automatic medical report generation (AMRG), offer a promising solution to this dilemma. This review comprehensively examines AMRG methods from 2021 to 2024. It (i) presents solutions to primary challenges in this field, (ii) explores AMRG applications across various imaging modalities, (iii) introduces publicly available datasets, (iv) outlines evaluation metrics, (v) identifies techniques that significantly enhance model performance, and (vi) discusses unresolved issues and potential future research directions. This paper aims to provide a comprehensive understanding of the existing literature and inspire valuable future research.