Matthew Ng

发表

Cardiac MRI segmentation with sparse annotations: Ensembling deep learning uncertainty and shape priors

F. Guo, Grey Kuling, Matthew Ng, 2022, Medical Image Anal..

MR Imaging and Electrophysiological Features of Doxorubicin-Induced Fibrosis: Protocol Development in a Small Preclinical Pig Study with Histological Validation

M. Pop, I. Roifman, J. Barry, 2022, Applied Sciences.

Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study

S. Petersen, S. Piechnik, G. Wright, 2020, IEEE Transactions on Biomedical Engineering.

Pipeline to Build and Test Robust 3D T1 Mapping-Based Heart Models for EP Interventions: Preliminary Results

Mengyuan Li, Maxime Sermesant, Mihaela Pop, 2019, FIMH.

Loss odyssey in medical image segmentation

Anne L. Martel, Rui Huang, Jun Ma, 2021, Medical Image Anal..

Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach

Stefan Neubauer, Maged Goubran, Fumin Guo, 2020, Medical Image Anal..

Cardiac Magnetic Resonance Left Ventricle Segmentation and Function Evaluation Using a Trained Deep-Learning Model

G. Wright, I. Roifman, F. Guo, 2022, Applied Sciences.

Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data

Georgios Tziritas, Eric Kerfoot, Jin Ma, 2021, IEEE Journal of Biomedical and Health Informatics.

Novel Imaging Biomarkers to Evaluate Heart Dysfunction Post-chemotherapy: A Preclinical MRI Feasibility Study

Mihaela Pop, Jennifer Barry, Terenz Escartin, 2021, STACOM@MICCAI.

Cardiac MRI Left Ventricle Segmentation and Quantification: A Framework Combining U-Net and Continuous Max-Flow

Graham A. Wright, Matthew Ng, Fumin Guo, 2018, STACOM@MICCAI.