Artificial Intelligence in Medical Imaging

• Dr. Kenji Tanaka

  Department of Biomedical Engineering University of Tokyo Tokyo, Japan

  Author

Medical imaging is central to modern diagnosis and clinical decision making. In recent years, artificial intelligence (AI), particularly deep learning, has transformed the analysis and interpretation of medical images across radiology, pathology, and cardiology. This paper examines recent advances in AI-driven medical imaging, focusing on diagnostic accuracy, workflow efficiency, and clinical integration. Drawing on peer-reviewed studies published between 2023 and 2025, the paper reviews applications of AI in radiology, oncology, and diagnostic pathology, and evaluates challenges related to data quality, ethics, and regulatory approval. The analysis demonstrates that AI systems can significantly enhance diagnostic precision and reduce clinician workload when appropriately validated and implemented. The paper concludes by discussing future research directions and the implications of AI adoption for healthcare systems worldwide.

• pdf

This work is licensed under a Creative Commons Attribution 4.0 International License.

You are free to:

1. Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
2. Adapt — remix, transform, and build upon the material for any purpose, even commercially.
3. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

1. Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
2. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.