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Progress in deep learning based on magnetic resonance imaging for rectal cancer research
SHI Shengming  XIAO Lingqing  MA Jiaqi  LIU Han  Wu Yupeng  LI Xiaofu 

Cite this article as: SHI S M, XIAO L Q, MA J Q, et al. Progress in deep learning based on magnetic resonance imaging for rectal cancer research[J]. Chin J Magn Reson Imaging, 2024, 15(3): 218-222. DOI:10.12015/issn.1674-8034.2024.03.036.


[Abstract] Rectal cancer (RC) is a malignancy with a high incidence rate worldwide, posing significant challenges in its management and treatment. MRI is the conventional modality used to assess RC. However, both traditional MRI and functional MRI frequently fall short in providing sufficient information for the development of personalized treatment plans for RC patients due to their inherent limitations. With the rapid advancements in artificial intelligence within the medical field in recent years, deep learning technologies have demonstrated tremendous potential and broad prospects for applications in areas such as RC staging, treatment response evaluation, RC segmentation, and genetic typing. These advancements suggest that deep learning could pave new ways for enhancing the precision and personalization of treatment decisions in RC in the future. This article presents a comprehensive review on the application of MRI-based deep learning techniques in RC, aiming to assist in selecting the optimal treatment strategy for RC patients, thereby improving patient outcomes, and providing new insights and directions for future research endeavors.
[Keywords] rectal cancer；magnetic resonance imaging；deep learning；predicted performance

SHI Shengming1   XIAO Lingqing2   MA Jiaqi1   LIU Han1   Wu Yupeng1   LI Xiaofu1*  

1 Department of Magnetic resonance imaging diagnostic, the 2nd Affiliated Hospital of Harbin Medical University, Harbin 150086, China

2 Medical Imaging Center, General Hospital, Beitun Hospital, 10th Division, Xinjiang Production and Construction Corps, Beitun 836099, China

Corresponding author: LI X F, E-mail: davin2004@163.com

Conflicts of interest   None.

Received  2023-12-04
Accepted  2024-02-05
DOI: 10.12015/issn.1674-8034.2024.03.036
Cite this article as: SHI S M, XIAO L Q, MA J Q, et al. Progress in deep learning based on magnetic resonance imaging for rectal cancer research[J]. Chin J Magn Reson Imaging, 2024, 15(3): 218-222. DOI:10.12015/issn.1674-8034.2024.03.036.

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