8 papers
Equivariant symmetry-aware head pose estimation for fetal MRI
Ramya Muthukrishnan, Borjan Gagoski, Aryn Lee +4
We present E(3)-Pose, a novel fast pose estimation method that jointly and explicitly models rotation equivariance and object symmetry. Our work is motivated by the challenging pro…
Volumetrically Consistent Implicit Atlas Learning via Neural Diffeomorphic Flow for Placenta MRI
Athena Taymourtash, S. Mazdak Abulnaga, Esra Abaci Turk +2
Establishing dense volumetric correspondences across anatomical shapes is essential for group-level analysis but remains challenging for implicit neural representations. Most exist…
Aligning Fetal Anatomy with Kinematic Tree Log-Euclidean PolyRigid Transforms
Yingcheng Liu, Athena Taymourtash, Yang Liu +5
Automated analysis of articulated bodies is crucial in medical imaging. Existing surface-based models often ignore internal volumetric structures and rely on deformation methods th…
Fast Multi-Stack Slice-to-Volume Reconstruction via Multi-Scale Unrolled Optimization
Margherita Firenze, Sean I. Young, Clinton J. Wang +5
Fully convolutional networks have become the backbone of modern medical imaging due to their ability to learn multi-scale representations and perform end-to-end inference. Yet thei…
Robust Fetal Pose Estimation across Gestational Ages via Cross-Population Augmentation
Sebastian Diaz, Benjamin Billot, Neel Dey +5
Fetal motion is a critical indicator of neurological development and intrauterine health, yet its quantification remains challenging, particularly at earlier gestational ages (GA).…
Fetuses Made Simple: Modeling and Tracking of Fetal Shape and Pose
Yingcheng Liu, Peiqi Wang, Sebastian Diaz +4
Analyzing fetal body motion and shape is paramount in prenatal diagnostics and monitoring. Existing methods for fetal MRI analysis mainly rely on anatomical keypoints or volumetric…