10 citations · 26 across the 13 of their papers we have counts for
7 papers · 1 filter
Neural Pre-Processing: A Learning Framework for End-to-end Brain MRI Pre-processing
Xinzi He, Alan Wang, Mert R. Sabuncu
Head MRI pre-processing involves converting raw images to an intensity-normalized, skull-stripped brain in a standard coordinate space. In this paper, we propose an end-to-end weak…
Hyper-Convolutions via Implicit Kernels for Medical Imaging
Tianyu Ma, Alan Q. Wang, Adrian V. Dalca +1
The convolutional neural network (CNN) is one of the most commonly used architectures for computer vision tasks. The key building block of a CNN is the convolutional kernel that ag…
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…
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…
Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data
Alan Q. Wang, Adrian V. Dalca, Mert R. Sabuncu
Compressed Sensing MRI (CS-MRI) has shown promise in reconstructing under-sampled MR images, offering the potential to reduce scan times. Classical techniques minimize a regularize…
Extending LOUPE for K-space Under-sampling Pattern Optimization in Multi-coil MRI
Jinwei Zhang, Hang Zhang, Alan Wang +5
The previously established LOUPE (Learning-based Optimization of the Under-sampling Pattern) framework for optimizing the k-space sampling pattern in MRI was extended in three fold…