Wensha Yang

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Associate Professor

University of California, San Francisco

United States

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Wensha Yang is an Associate Professor at the University of California, San Francisco. His research areas include advanced MRI techniques, radiotherapy treatment planning, and machine learning applications in medical imaging. Recent publications highlight his work on multi-contrast MRI, voxel-wise predictions for brain tumors, and the integration of generative adversarial networks for enhanced imaging modalities.

Recent Grants

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Multi-Task MR Simulation for Abdominal Radiation Treatment Planning

Open Date: 2020-07-01

Close Date: 2024-03-31

Grant: Close

Novel four dimensional magnetic resonance imaging to monitor pancreatic tumor infiltrating blood vessels and tumor response to chemoradiation therapy

Open Date: 2019-07-17

Close Date: 2021-06-30

Grant: Close

Improving Pancreas RT Plans using Respiration-driven Anatomic Deformation

Open Date: 2013-02-01

Close Date: 2015-07-31

Wensha Yang

Research Interests

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About

Recent Grants

Articles (22)

Multi-contrast 4DMR via MR multitasking: Early clinical experience and implication for liver stereotactic body radiation therapy

Accelerated Patient-specific Non-Cartesian MRI Reconstruction using Implicit Neural Representations

Paired conditional generative adversarial network for highly accelerated liver 4D MRI

Abdominal MR Multitasking for radiotherapy treatment planning: A motion‐resolved and multicontrast 3D imaging approach

Multi-modal fusion and feature enhancement U-Net coupling with stem cell niches proximity estimation for voxel-wise GBM recurrence prediction *

A repository of grade 1 and 2 meningioma MRIs in a public dataset for radiomics reproducibility tests.

4pi Treatment Planning Strategy Regularized by Voxel-Wise T1 Reduction Rate for Liver Function Avoidance SBRT

Assessing the Tumor Visibility and Respiratory Motion of Liver Cancer Patients on Multi-Task MR and 4D-CT Imaging for Radiation Treatment Planning

Semantic modeling of hyperspectral target detection with weak labels

Contrast-Enhanced Liver Magnetic Resonance Image Synthesis Using Gradient Regularized Multi-Modal Multi-Discrimination Sparse Attention Fusion GAN

MR multitasking‐based dynamic imaging for cerebrovascular evaluation (MT‐DICE): Simultaneous quantification of permeability and leakage‐insensitive perfusion by dynamic T1/T2* mapping

A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength

Contouring Analysis on Synthetic Contrast-Enhanced MR from GRMM-GAN and Implications on MR-Guide Radiation Therapy

Single projection driven real-time multi-contrast (SPIDERM) MR imaging using pre-learned spatial subspace and linear transformation

Automatic differentiation of Grade I and II meningiomas on magnetic resonance image using an asymmetric convolutional neural network

Automatic segmentation of high-risk clinical target volume for tandem-and-ovoids brachytherapy patients using an asymmetric dual-path convolutional neural network

Voxelwise Prediction of Recurrent High-Grade Glioma via Proximity Estimation–Coupled Multidimensional Support Vector Machine

Biomedical Profiling of Lung Tumor via Ventilation-Induced Tumor Deformation: Implications on the Prognosis of Lung Cancer

Comparison of an Auto-Segmentation Model Using a Dual-Path Convolutional Neural Network to Intra- and Inter-Operator High-Risk Clinical Target Volumes for Tandem-and-Ovoid Brachytherapy

Quantitative Characterization of Tumor Proximity to Stem Cell Niches: Implications on Recurrence and Survival in GBM Patients.

Automatic detection and segmentation of multiple brain metastases on magnetic resonance image using asymmetric UNet architecture.

Bladder surface dose modeling in prostate cancer radiotherapy: An analysis of motion-induced variations and the cumulative dose across the treatment

Collaborators (3)

DI XU

Yang Yang

Anthony Christodoulou

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