37 citations · 41 across the 10 of their papers we have counts for
7 papers · 1 filter
Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction
Shijie Li, Palaiologos Alexopoulos, Anse Vellappally +3
Strong speckle noise is inherent to optical coherence tomography (OCT) imaging and represents a significant obstacle for accurate quantitative analysis of retinal structures which…
-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…
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…