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BMC Med Imaging2025;25(1):259.July 1, 2025Journal Article

Preoperative MRI-based deep learning reconstruction and classification model for assessing rectal cancer.

Yuan Yuan1, Shengnan Ren2, Haidi Lu1, Fangying Chen1, Lei Xiang3, Ryan Chamberlain4, Chengwei Shao1, Jianping Lu5, Fu Shen6, Luguang Chen7
1Department of Radiology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China.
2Department of Nuclear Medicine, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, 200434, China.
3Department of Research and Development, Subtle Medical, Shanghai, China.
4Department of Research and Development, Subtle Medical, Menlo Park, CA, USA.
5Department of Radiology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China. cjr.lujianping@vip.163.com.
6Department of Radiology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China. ssff_53@163.com.
7Department of Radiology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China. chen_lu_guang@sina.com.
PubMed PMC DOI PDF

Abstract

BACKGROUND: To determine whether deep learning reconstruction (DLR) could improve the image quality of rectal MR images, and to explore the discrimination of the TN stage of rectal cancer by different readers and deep learning classification models, compared with conventional MR images without DLR. METHODS: Images of high-resolution T2-weighted, diffusion-weighted imaging (DWI), and contrast-enha…

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