ARTICLE
Volume 4,Issue 2
30 June 2026
A Review of Research Progress and Challenges in Deep Learning for Magnetic Resonance Imaging in the Diagnosis and Treatment of Prostate Cancer
Xiao Yuan
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1
School of Gongli Hospital Medical Technology, University of Shanghai for Science and Technology, Shanghai 200093, China,
OTD 2026 , 4(2), 52–59;
https://doi.org/10.26689/otd.v4i2.15406
© 2026 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract
Prostate cancer is a highly prevalent malignant tumor among men worldwide, and its precise diagnosis and treatment are crucial for improving patient prognosis. Multiparametric magnetic resonance imaging, as a core imaging modality, is widely used in clinical practice. In recent years, breakthroughs in deep learning technology have provided powerful tools for the intelligent analysis of MRI images, promoting the development of automated and precise diagnosis and treatment for prostate cancer. This article aims to systematically review the current applications of deep learning in the field of prostate cancer MRI, covering key directions such as lesion detection and segmentation, diagnosis and grading, prognosis prediction, and imaging genomics correlation. The article provides an in-depth analysis of current mainstream models, the challenges related to data and validation, and offers insights into future trends, with the goal of providing references for related research and clinical practice.
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