activity
20202026
most citedIntraoperative 2D/3D Image Registration via Differentiable X-ray Rendering

42 citations · 171 across the 31 of their papers we have counts for

collaborators
Showing 2023Show all

10 papers · 1 filter

eess.IV2023★ 6 cited

Shape-aware Segmentation of the Placenta in BOLD Fetal MRI Time Series

S. Mazdak Abulnaga, Neel Dey, Sean I. Young +6

Blood oxygen level dependent (BOLD) MRI time series with maternal hyperoxia can assess placental oxygenation and function. Measuring precise BOLD changes in the placenta requires a…

eess.IV2023★ 11 cited

SE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI

Benjamin Billot, Neel Dey, Daniel Moyer +5

Rigid motion tracking is paramount in many medical imaging applications where movements need to be detected, corrected, or accounted for. Modern strategies rely on convolutional ne…

cs.CV2023★ 42 cited

Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering

Vivek Gopalakrishnan, Neel Dey, Polina Golland

Surgical decisions are informed by aligning rapid portable 2D intraoperative images (e.g., X-rays) to a high-fidelity 3D preoperative reference scan (e.g., CT). 2D/3D image registr…

eess.IV2023★ 3 cited

Dynamic Neural Fields for Learning Atlases of 4D Fetal MRI Time-series

Zeen Chi, Zhongxiao Cong, Clinton J. Wang +6

We present a method for fast biomedical image atlas construction using neural fields. Atlases are key to biomedical image analysis tasks, yet conventional and deep network estimati…

cs.CV2023

Consistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series

Yingcheng Liu, Neerav Karani, Neel Dey +5

The placenta plays a crucial role in fetal development. Automated 3D placenta segmentation from fetal EPI MRI holds promise for advancing prenatal care. This paper proposes an effe…

cs.CV2023

Boundary-weighted logit consistency improves calibration of segmentation networks

Neerav Karani, Neel Dey, Polina Golland

Neural network prediction probabilities and accuracy are often only weakly-correlated. Inherent label ambiguity in training data for image segmentation aggravates such miscalibrati…

cs.CV2023

AnyStar: Domain randomized universal star-convex 3D instance segmentation

Neel Dey, S. Mazdak Abulnaga, Benjamin Billot +4

Star-convex shapes arise across bio-microscopy and radiology in the form of nuclei, nodules, metastases, and other units. Existing instance segmentation networks for such structure…

eess.IV2023

-Equivariant Networks for Spherical Deconvolution in Diffusion MRI

Axel Elaldi, Guido Gerig, Neel Dey

We present Roto-Translation Equivariant Spherical Deconvolution (RT-ESD), an equivariant framework for sparse deconvolution of volumes where each voxel contains…

eess.IV2023

Dual-Domain Self-Supervised Learning for Accelerated Non-Cartesian MRI Reconstruction

Bo Zhou, Jo Schlemper, Neel Dey +5

While enabling accelerated acquisition and improved reconstruction accuracy, current deep MRI reconstruction networks are typically supervised, require fully sampled data, and are…

eess.IV2023★ 11 cited

Data Consistent Deep Rigid MRI Motion Correction

Nalini M. Singh, Neel Dey, Malte Hoffmann +5

Motion artifacts are a pervasive problem in MRI, leading to misdiagnosis or mischaracterization in population-level imaging studies. Current retrospective rigid intra-slice motion…