37 citations · 56 across the 14 of their papers we have counts for
14 papers
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…
Microscopy Image Segmentation via Point and Shape Regularized Data Synthesis
Shijie Li, Mengwei Ren, Thomas Ach +1
Current deep learning-based approaches for the segmentation of microscopy images heavily rely on large amount of training data with dense annotation, which is highly costly and lab…
-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…
Multiscale Structure Guided Diffusion for Image Deblurring
Mengwei Ren, Mauricio Delbracio, Hossein Talebi +2
Diffusion Probabilistic Models (DPMs) have recently been employed for image deblurring, formulated as an image-conditioned generation process that maps Gaussian noise to the high-q…
ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration
Neel Dey, Jo Schlemper, Seyed Sadegh Mohseni Salehi +3
Establishing voxelwise semantic correspondence across distinct imaging modalities is a foundational yet formidable computer vision task. Current multi-modality registration techniq…
Local Spatiotemporal Representation Learning for Longitudinally-consistent Neuroimage Analysis
Mengwei Ren, Neel Dey, Martin A. Styner +2
Recent self-supervised advances in medical computer vision exploit global and local anatomical self-similarity for pretraining prior to downstream tasks such as segmentation. Howev…
Improved Counting and Localization from Density Maps for Object Detection in 2D and 3D Microscopy Imaging
Shijie Li, Thomas Ach, Guido Gerig
Object counting and localization are key steps for quantitative analysis in large-scale microscopy applications. This procedure becomes challenging when target objects are overlapp…
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…
Generative Adversarial Registration for Improved Conditional Deformable Templates
Neel Dey, Mengwei Ren, Adrian V. Dalca +1
Deformable templates are essential to large-scale medical image registration, segmentation, and population analysis. Current conventional and deep network-based methods for templat…
Point-supervised Segmentation of Microscopy Images and Volumes via Objectness Regularization
Shijie Li, Neel Dey, Katharina Bermond +4
Annotation is a major hurdle in the semantic segmentation of microscopy images and volumes due to its prerequisite expertise and effort. This work enables the training of semantic…
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…
A framework to construct a longitudinal DW-MRI infant atlas based on mixed effects modeling of dODF coefficients
Heejong Kim, Martin Styner, Joseph Piven +1
Building of atlases plays a crucial role in the analysis of brain images. In scenarios where early growth, aging or disease trajectories are of key importance, longitudinal atlases…