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Automatic Removal of Externally Attached Fiducial Markers in Cone Beam C-Arm CT.

, , , , , , , и . Bildverarbeitung für die Medizin, стр. 318-323. Springer, (2014)

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Jang-Hwan Im

Sung-Hwan Choi

Liem Khiem Jang

Tae-Seok Jang

Saeed Jangani

 

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Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-beam CT., , , , , , , , , и . CoRR, (2019)Comparison of Different Approaches for Measuring Tibial Cartilage Thickness., , , , , , , , , и . J. Integr. Bioinform., (2017)Deep Learning with Multimodal Integration for Predicting Recurrence in Patients with Non-Small Cell Lung Cancer., , и . Sensors, 22 (17): 6594 (2022)Abstract: Inertial Measurements for Motion Compensation in Weight-bearing Cone-beam CT of the Knee., , , , , , и . Bildverarbeitung für die Medizin, стр. 336. Springer, (2021)Inertial Measurements for Motion Compensation in Weight-Bearing Cone-Beam CT of the Knee., , , , , , и . MICCAI (3), том 12263 из Lecture Notes in Computer Science, стр. 14-23. Springer, (2020)Integration of 2D iteration and a 3D CNN-based model for multi-type artifact suppression in C-arm cone-beam CT., , , , , и . Mach. Vis. Appl., 32 (6): 116 (2021)Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT., , , , , , , , , и . Bildverarbeitung für die Medizin, стр. 67-72. Springer, (2020)Precision Learning: Towards Use of Known Operators in Neural Networks., , , , , , и . ICPR, стр. 183-188. IEEE Computer Society, (2018)Anatomical Landmark Detection Using a Multiresolution Learning Approach with a Hybrid Transformer-CNN Model., , и . MICCAI (6), том 14225 из Lecture Notes in Computer Science, стр. 433-443. Springer, (2023)Noise2Contrast: Multi-contrast Fusion Enables Self-supervised Tomographic Image Denoising., , , , , , , , , и 3 other автор(ы). IPMI, том 13939 из Lecture Notes in Computer Science, стр. 771-782. Springer, (2023)