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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…
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,…
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…
Hyper-Convolution Networks for Biomedical Image Segmentation
Tianyu Ma, Adrian V. Dalca, Mert R. Sabuncu
The convolution operation is a central building block of neural network architectures widely used in computer vision. The size of the convolution kernels determines both the expres…
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…
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…
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…