activity
20172020
most citedCombating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation

9 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2020

Computer-aided Tumor Diagnosis in Automated Breast Ultrasound using 3D Detection Network

Junxiong Yu, Chaoyu Chen, Xin Yang +4

Automated breast ultrasound (ABUS) is a new and promising imaging modality for breast cancer detection and diagnosis, which could provide intuitive 3D information and coronal plane…

eess.IV20208 cited

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…

eess.IV20203 cited

Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping

Jinwei Zhang, Hang Zhang, Mert Sabuncu +3

A learning-based posterior distribution estimation method, Probabilistic Dipole Inversion (PDI), is proposed to solve quantitative susceptibility mapping (QSM) inverse problem in M…

cs.CV20189 cited

Combating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation

Xin Yang, Na Wang, Yi Wang +4

Segmenting left atrium in MR volume holds great potentials in promoting the treatment of atrial fibrillation. However, the varying anatomies, artifacts and low contrasts among tiss…

physics.med-ph20173 cited

Dipole Incompatibility Related Artifacts in Quantitative Susceptibility Mapping

Liangdong Zhou, Jae Kyu Choi, Youngwook Kee +2

Artifacts in quantitative susceptibility mapping (QSM) are analyzed to establish an optimal design criterion for QSM inversion algorithms. The magnetic field data is decomposed int…