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Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT.

, , , , , , , , , and . Bildverarbeitung für die Medizin, page 67-72. Springer, (2020)

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Detecting Anatomical Landmarks for Motion Estimation in Weight-Bearing Imaging of Knees., , , , , , , and . MLMIR@MICCAI, volume 11074 of Lecture Notes in Computer Science, page 83-90. Springer, (2018)Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT., , , , , , , , , and . Bildverarbeitung für die Medizin, page 67-72. Springer, (2020)A Framework for Evaluating Myocardial Stiffness Using 3D-Printed Heart Phantoms., , , , , , , and . FIMH, volume 12738 of Lecture Notes in Computer Science, page 305-314. Springer, (2021)Smooth Ride: Low-Pass Filtering of Manual Segmentations Improves Consensus., , , , , , , , and . Bildverarbeitung für die Medizin, page 86-91. Springer Vieweg, (2019)Comparison of Different Approaches for Measuring Tibial Cartilage Thickness., , , , , , , , , and . J. Integr. Bioinform., (2017)Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-beam CT., , , , , , , , , and . CoRR, (2019)Motion Compensation Using Range Imaging in C-Arm Cone-Beam CT., , , , , , , and . MIUA, volume 723 of Communications in Computer and Information Science, page 561-570. Springer, (2017)Epipolar Consistency Conditions for Motion Correction in Weight-Bearing Imaging., , , , , , , and . Bildverarbeitung für die Medizin, page 209-214. Springer, (2017)