| For: | Takayama Y, Sato K, Tanaka S, Murayama R, Goto N, Yoshimitsu K. Deep learning-based magnetic resonance imaging reconstruction for improving the image quality of reduced-field-of-view diffusion-weighted imaging of the pancreas. World J Radiol 2023; 15(12): 338-349 [PMID: 38179202 DOI: 10.4329/wjr.v15.i12.338] |
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| URL: | https://www.wjgnet.com/1948-5182/full/v15/i12/338.htm |
| Number | Citing Articles |
| 1 |
Kazuki Oyama, Fumihito Ichinohe, Yasuo Adachi, Yoshihiro Kito, Katsuya Maruyama, Minoru Mitsuda, Thomas Benkert, Omar Darwish, Yasunari Fujinaga. Improvement of image quality of diffusion-weighted imaging (DWI) with deep learning reconstruction of the pancreas: comparison with respiratory-gated conventional DWI. Japanese Journal of Radiology 2025; 43(9): 1509 doi: 10.1007/s11604-025-01790-w
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| 2 |
Fateme Hoseini Rashkani, Abbas Nasiraei Moghaddam. Accelerated Diffusion-Weighted Imaging via Diffusion Gradient Alternation in Radial k-Space Sampling. 2025 32nd National and 10th International Iranian Conference on Biomedical Engineering (ICBME) 2025; : 1149 doi: 10.1109/ICBME68496.2025.11392574
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| 3 |
Yukihisa Takayama, Keisuke Sato, Shinji Tanaka, Ryo Murayama, Ryotaro Jingu, Kengo Yoshimitsu. Effectiveness of deep learning-based reconstruction for improvement of image quality and liver tumor detectability in the hepatobiliary phase of gadoxetic acid-enhanced magnetic resonance imaging. Abdominal Radiology 2024; 49(10): 3450 doi: 10.1007/s00261-024-04374-w
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| 4 |
Junhao Lee, Tingting Lin, Yifei He, Ye Wu, Jiaolong Qin. Toward diffusion MRI in the diagnosis and treatment of pancreatic cancer. Medical Oncology 2025; 42(7) doi: 10.1007/s12032-025-02759-5
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| 5 |
Jian-She Yang, Qiang Wang, Zhong-Wei Lv. Artificial intelligence for disease diagnostics still has a long way to go. World Journal of Radiology 2024; 16(3): 69-71 doi: 10.4329/wjr.v16.i3.69
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| 6 |
Yoshisuke Kadoya, Kentaro Mochizuki, Akihiro Asano, Kosuke Miyakawa, Mao Kanatani, Junko Saito, Hitoshi Abo. MRI sequence focused on pancreatic morphology evaluation: three-shot turbo spin-echo with deep learning-based reconstruction. Acta Radiologica 2025; 66(11): 1184 doi: 10.1177/02841851251355844
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| 7 |
Xue Dong, Dongmei Shi, Zhiwei Qin, Huifang Yong, Qiufeng Yin, Peirong Zhang, Zhongyang Zhang, Xing Zhang, Shaofeng Duan, Dengbin Wang, Huanhuan Liu. Comparison of reduced FOV diffusion-weighted imaging of rectal cancer at 5.0T ultra-high field versus 3.0T MRI: image quality and histopathological T staging. BMC Medical Imaging 2025; 26(1) doi: 10.1186/s12880-025-02076-3
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| 8 |
Nan Wang, Miaotong Liu, Wenhui Wang, Ying Zhao, Jun Li, Xue Ren, Dan Yu, Ailian Liu, Xiukun Hou, Qingwei Song. Accelerated Reduced Field of View T2-Weighted Imaging of Pancreaticobiliary Disorders Using Deep Learning-Based Reconstruction: Reduction of Acquisition Time and Improvement of Image Quality. Canadian Association of Radiologists Journal 2026; doi: 10.1177/08465371251407889
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| 9 |
Simona Marzi, Vicente Bruzzaniti, Francesca Laganaro, Giovanni Di Giulio, Michele Farella, Alessia Tonnetti, Irene Terrenato, Roberto Castellana, Antonello Vidiri. Impact of deep learning image reconstruction on ADC quantification and histogram metrics: a phantom study. European Radiology Experimental 2026; 10(1) doi: 10.1186/s41747-026-00709-y
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