activity
20192025
most citedFetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network

6 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

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).…

eess.IV2024★ 1 cited

FetalDiffusion: Pose-Controllable 3D Fetal MRI Synthesis with Conditional Diffusion Model

Molin Zhang, Polina Golland, Patricia Ellen Grant +1

The quality of fetal MRI is significantly affected by unpredictable and substantial fetal motion, leading to the introduction of artifacts even when fast acquisition sequences are…

eess.IV2023★ 2 cited

Zero-Shot Self-Supervised Joint Temporal Image and Sensitivity Map Reconstruction via Linear Latent Space

Molin Zhang, Junshen Xu, Yamin Arefeen +1

Fast spin-echo (FSE) pulse sequences for Magnetic Resonance Imaging (MRI) offer important imaging contrast in clinically feasible scan times. T2-shuffling is widely used to resolve…

cs.CV2020★ 2 cited

Enhanced detection of fetal pose in 3D MRI by Deep Reinforcement Learning with physical structure priors on anatomy

Molin Zhang, Junshen Xu, Esra Abaci Turk +3

Fetal MRI is heavily constrained by unpredictable and substantial fetal motion that causes image artifacts and limits the set of viable diagnostic image contrasts. Current mitigati…

eess.IV2019★ 6 cited

Fetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network

Junshen Xu, Molin Zhang, Esra Abaci Turk +5

The performance and diagnostic utility of magnetic resonance imaging (MRI) in pregnancy is fundamentally constrained by fetal motion. Motion of the fetus, which is unpredictable an…