Reduction of Motion Artifacts in Liver MRI Using Deep Learning with High-pass Filtering
Author:
Affiliation:
1. Department of Radiology, Fukuoka University Chikushi Hospital
Publisher
Japanese Society of Radiological Technology
Link
https://www.jstage.jst.go.jp/article/jjrt/80/5/80_2024-1408/_pdf
Reference21 articles.
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2. 2） Reimer P, Rummeny EJ, Daldrup HE, et al. Enhancement characteristics of liver metastases, hepatocellular carcinomas, and hemangiomas with Gd-EOB-DTPA: preliminary results with dynamic MR imaging. Eur Radiol 1997; 7(2): 275–280.
3. 3） van Kessel CS, Veldhuis WB, van den Bosch MAAJ, et al. MR liver imaging with Gd-EOB-DTPA: a delay time of 10 minutes is sufficient for lesion characterization. Eur Radiol 2012; 22(10): 2153–2160.
4. 4） Stadler A, Schima W, Ba-Ssalamah A, et al. Artifacts in body MR imaging: their appearance and how to eliminate them. Eur Radiol 2007; 17(5): 1242–1255.
5. 5） Chavhan GB, Babyn PS, Vasanawala SS. Abdominal MR imaging in children: motion compensation, sequence optimization, and protocol organization. Radiographics 2013; 33(3): 703–719.
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