activity
20182021
most citedAnatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

108 citations · 209 across the 17 of their papers we have counts for

collaborators

41 papers

q-bio.NC2021

Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query

Gia H. Ngo, Minh Nguyen, Nancy F. Chen +1

Most neuroimaging experiments are under-powered, limited by the number of subjects and cognitive processes that an individual study can investigate. Nonetheless, over decades of re…

cs.LG20212 cited

Ex uno plures: Splitting One Model into an Ensemble of Subnetworks

Zhilu Zhang, Vianne R. Gao, Mert R. Sabuncu

Monte Carlo (MC) dropout is a simple and efficient ensembling method that can improve the accuracy and confidence calibration of high-capacity deep neural network models. However,…

q-bio.NC20214 cited

NeuroGen: activation optimized image synthesis for discovery neuroscience

Zijin Gu, Keith W. Jamison, Meenakshi Khosla +6

Functional MRI (fMRI) is a powerful technique that has allowed us to characterize visual cortex responses to stimuli, yet such experiments are by nature constructed based on a prio…

eess.IV2021

Joint Optimization of Hadamard Sensing and Reconstruction in Compressed Sensing Fluorescence Microscopy

Alan Q. Wang, Aaron K. LaViolette, Leo Moon +2

Compressed sensing fluorescence microscopy (CS-FM) proposes a scheme whereby less measurements are collected during sensing and reconstruction is performed to recover the image. Mu…

eess.SP20211 cited

Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction

Jinwei Zhang, Hang Zhang, Chao Li +4

Quantitative imaging in MRI usually involves acquisition and reconstruction of a series of images at multi-echo time points, which possibly requires more scan time and specific rec…

eess.IV202110 cited

Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks

Alan Q. Wang, Adrian V. Dalca, Mert R. Sabuncu

Reconstructing under-sampled k-space measurements in Compressed Sensing MRI (CS-MRI) is classically solved with regularized least-squares. Recently, deep learning has been used to…