Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
565-05-002 ISMRM Abstract

Comparative Study of Manual Versus Automated MRI-Based Tumor Segmentation and Staging in Rectal Cancer

Primary: Analysis Methods - Classification and Prediction
Secondary: Body - Digestive
565-05-002 · Segmentation for Body Applications · Wednesday, 13 May, 4:00 PM–4:55 PM · Digital Posters Row F
Keywords: Radiomics MRI Automated segmentation Tumor grading Colorectal cancer
Accepted
Yen-Chun Chen 1, Chi-Feng Hsieh2, Chia-Ching Chang2, Chun-Jung Juan1,2, Yi-Jui Liu3, Hsu-Hsia Peng1
1Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan
2Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, Hsinchu City, Taiwan
3Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan
Presenting Author: Yen-Chun Chen

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References

1. Engelen SM, Beets-Tan RG, Lahaye MJ, et al. MRI after chemoradiotherapy of rectal cancer: a useful tool to select patients for local excision. Dis Colon Rectum. Jul 2010;53(7):979-86. doi:10.1007/DCR.0b013e3181dc64dc [doi]
2. Lambregts DM, Vandecaveye V, Barbaro B, et al. Diffusion-weighted MRI for selection of complete responders after chemoradiation for locally advanced rectal cancer: a multicenter study. Ann Surg Oncol. Aug 2011;18(8):2224-31. doi:10.1245/s10434-011-1607-5 [doi]
3. Zhu HT, Zhang XY, Shi YJ, Li XT, Sun YS. Automatic segmentation of rectal tumor on diffusion‐weighted images by deep learning with U‐Net. Journal of Applied Clinical Medical Physics. 2021;22(9):324-331.
4. Fan L, Wu H, Wu Y, Wu S, Zhao J, Zhu X. Preoperative prediction of rectal Cancer staging combining MRI deep transfer learning, radiomics features, and clinical factors: accurate differentiation from stage T2 to T3. BMC Gastroenterol. Aug 5 2024;24(1):247. doi:10.1186/s12876-024-03316-6 [doi]
5. Zhu Y, Wei Y, Chen Z, et al. Different radiomics annotation methods comparison in rectal cancer characterisation and prognosis prediction: a two-centre study. Insights Imaging. Aug 26 2024;15(1):211. doi:10.1186/s13244-024-01795-5 [doi]
6. Gurses B, Boge M, Altinmakas E, Balik E. Multiparametric MRI in rectal cancer. Diagn Interv Radiol. May 2019;25(3):175-182. doi:10.5152/dir.2019.18189 [doi]
7. Ao W, Wu S, Mao G, et al. Can Habitat-Based MRI Radiomics Distinguish Between T2 and T3 Stages in Rectal Cancer? Acad Radiol. Sep 2025;32(9):5278-5289. doi:10.1016/j.acra.2025.04.017 [doi]
8. Nougaret S, Jhaveri K, Kassam Z, Lall C, Kim DH. Rectal cancer MR staging: pearls and pitfalls at baseline examination. Abdominal Radiology. 2019;44:3536-3548.

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http://echo.ismrm.org/p/ISMRM2026/565-05-002