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Efficient Deformable Motion Correction for 3-D Abdominal MRI Using Manifold Regression.

, , , , , and . MICCAI (2), volume 10434 of Lecture Notes in Computer Science, page 270-278. Springer, (2017)

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Deep Learning Based Approach to Quantification of PET Tracer Uptake in Small Tumors., , , , and . MLMIR@MICCAI, volume 11905 of Lecture Notes in Computer Science, page 181-192. Springer, (2019)Dynamic Volume Reconstruction from Multi-slice Abdominal MRI Using Manifold Alignment., , , , , , and . MICCAI (3), volume 9902 of Lecture Notes in Computer Science, page 493-501. (2016)Validation of PET Imaging by Alignment to Histology Slices., , , , , , and . MICCAI (2), volume 3750 of Lecture Notes in Computer Science, page 968-975. Springer, (2005)Efficient Deformable Motion Correction for 3-D Abdominal MRI Using Manifold Regression., , , , , and . MICCAI (2), volume 10434 of Lecture Notes in Computer Science, page 270-278. Springer, (2017)High-Resolution Self-Gated Dynamic Abdominal MRI Using Manifold Alignment., , , , , , , and . IEEE Trans. Med. Imaging, 36 (4): 960-971 (2017)PET-MR respiratory signal estimation using semi-supervised manifold alignment., , , , , , , and . ISBI, page 599-603. IEEE, (2018)Evaluation of Strategies for PET Motion Correction - Manifold Learning vs. Deep Learning., , , , , and . MLCN/DLF/iMIMIC@MICCAI, volume 11038 of Lecture Notes in Computer Science, page 61-69. Springer, (2018)MRI slice stacking using manifold alignment and wave kernel signatures., , , , , and . ISBI, page 319-323. IEEE, (2018)