42 citations · 171 across the 31 of their papers we have counts for
17 papers · 1 filter
Why Invariance is Not Enough for Biomedical Domain Generalization and How to Fix It
Sebo Diaz, Polina Golland, Elfar Adalsteinsson +1
We present MaskGen, a theoretically grounded and deliberately simple approach for domain generalization in 3D biomedical image segmentation. Modern segmentation models degrade shar…
Rapid patient-specific neural networks for intraoperative X-ray to volume registration
Vivek Gopalakrishnan, David-Dimitris Chlorogiannis, Andrew Abumoussa +6
Advanced navigation techniques in image-guided interventions and surgical robotics require the rapid and precise alignment of 3D preoperative volumes (e.g., CT, MRI) to 2D intraope…
Differentiable Voxel-based X-ray Rendering Improves Sparse-View 3D CBCT Reconstruction
Mohammadhossein Momeni, Vivek Gopalakrishnan, Neel Dey +2
We present DiffVox, a self-supervised framework for Cone-Beam Computed Tomography (CBCT) reconstruction by directly optimizing a voxelgrid representation using physics-based differ…
Equivariant spatio-hemispherical networks for diffusion MRI deconvolution
Axel Elaldi, Guido Gerig, Neel Dey
Each voxel in a diffusion MRI (dMRI) image contains a spherical signal corresponding to the direction and strength of water diffusion in the brain. This paper advances the analysis…
VoxelPrompt: A Vision Agent for End-to-End Medical Image Analysis
Andrew Hoopes, Neel Dey, Victor Ion Butoi +2
We present VoxelPrompt, an end-to-end image analysis agent that tackles free-form radiological tasks. Given any number of volumetric medical images and a natural language prompt, V…
Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound
Yiming Chen, Niharika S. D'Souza, Akshith Mandepally +9
Precisely estimating lumen boundaries in intravascular ultrasound (IVUS) is needed for sizing interventional stents to treat deep vein thrombosis (DVT). Unfortunately, current segm…
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…
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…
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…
-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…
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…
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…
DSFormer: A Dual-domain Self-supervised Transformer for Accelerated Multi-contrast MRI Reconstruction
Bo Zhou, Neel Dey, Jo Schlemper +4
Multi-contrast MRI (MC-MRI) captures multiple complementary imaging modalities to aid in radiological decision-making. Given the need for lowering the time cost of multiple acquisi…
Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
Mengwei Ren, Heejong Kim, Neel Dey +1
Current deep learning approaches for diffusion MRI modeling circumvent the need for densely-sampled diffusion-weighted images (DWIs) by directly predicting microstructural indices…
Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data
Axel Elaldi, Neel Dey, Heejong Kim +1
We present a rotation-equivariant unsupervised learning framework for the sparse deconvolution of non-negative scalar fields defined on the unit sphere. Spherical signals with mult…
Segmentation-Renormalized Deep Feature Modulation for Unpaired Image Harmonization
Mengwei Ren, Neel Dey, James Fishbaugh +1
Deep networks are now ubiquitous in large-scale multi-center imaging studies. However, the direct aggregation of images across sites is contraindicated for downstream statistical a…
Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography
Guillaume Gisbert, Neel Dey, Hiroshi Ishikawa +3
Optical Coherence Tomography (OCT) is pervasive in both the research and clinical practice of Ophthalmology. However, OCT images are strongly corrupted by noise, limiting their int…