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Consistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series.

, , , , , , and . PIPPI@MICCAI, volume 14246 of Lecture Notes in Computer Science, page 77-87. Springer, (2023)

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