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Dynamic deformable attention network (DDANet) for COVID-19 lesions semantic segmentation.

, , and . J. Biomed. Informatics, (2021)

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GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs., and . IEEE Trans. Medical Imaging, 40 (9): 2246-2257 (2021)Multimodal 3D medical image registration guided by shape encoder-decoder networks., , and . Int. J. Comput. Assist. Radiol. Surg., 15 (2): 269-276 (2020)Attention gated networks: Learning to leverage salient regions in medical images., , , , , , and . Medical Image Anal., (2019)Anatomy-guided domain adaptation for 3D in-bed human pose estimation., , , , , and . Medical Image Anal., (October 2023)Self-supervised Learning of Dense Hierarchical Representations for Medical Image Segmentation., , and . CoRR, (2024)Chasing clouds: Differentiable volumetric rasterisation of point clouds as a highly efficient and accurate loss for large-scale deformable 3D registration., , , and . ICCV, page 7992-8002. IEEE, (2023)Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT., , , , , , , and . IEEE Trans. Biomed. Eng., 63 (8): 1563-1572 (2016)Topology-Preserving Shape-Based Regression Of Retinal Layers In Oct Image Data Using Convolutional Neural Networks., , , , and . ISBI, page 1437-1440. IEEE, (2019)Abstract: Advancing Large-scale Deformable 3D Registration with Differentiable Volumetric Rasterisation of Point Clouds - Chasing Clouds., , , and . Bildverarbeitung für die Medizin, page 101. Springer, (2024)Displacement Representation for Conditional Point Cloud Registration - HeatReg Applied to 2D/3D Freehand Ultrasound Reconstruction., , and . Bildverarbeitung für die Medizin, page 39-45. Springer, (2024)