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Consistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series., , , , , , , и . CoRR, (2023)Equivariant Filters for Efficient Tracking in 3D Imaging., , , , и . MICCAI (4), том 12904 из Lecture Notes in Computer Science, стр. 193-202. Springer, (2021)Fetal Pose Estimation in Volumetric MRI Using a 3D Convolution Neural Network., , , , , , , и . MICCAI (4), том 11767 из Lecture Notes in Computer Science, стр. 403-410. Springer, (2019)AnyStar: Domain randomized universal star-convex 3D instance segmentation., , , , , , и . WACV, стр. 7578-7588. IEEE, (2024)3D Fetal Pose Estimation with Adaptive Variance and Conditional Generative Adversarial Network., , , , , и . ASMUS/PIPPI@MICCAI, том 12437 из Lecture Notes in Computer Science, стр. 201-210. Springer, (2020)Placental Flattening via Volumetric Parameterization., , , , , и . MICCAI (4), том 11767 из Lecture Notes in Computer Science, стр. 39-47. Springer, (2019)Automatic Segmentation of the Placenta in BOLD MRI Time Series., , , , , , , и . PIPPI@MICCAI, том 13575 из Lecture Notes in Computer Science, стр. 1-12. Springer, (2022)Temporal Registration in Application to In-utero MRI Time Series., , , , , , и . CoRR, (2019)A Simple Analytical Expression for the Gradient Induced Potential on Active Implants During MRI., , , , , , и . IEEE Trans. Biomed. Eng., 59 (10): 2845-2851 (2012)STRESS: Super-Resolution for Dynamic Fetal MRI Using Self-supervised Learning., , , , и . MICCAI (7), том 12907 из Lecture Notes in Computer Science, стр. 197-206. Springer, (2021)