Research Interests

My major study area is signal & image processing and machine learning. My research interests include medical imaging, image reconstruction, inverse problems, optimization, and deep learning.

Journal Publications

• Deep Convolutional Neural Network With Adversarial Training for Denoising Digital Breast Tomosynthesis Images

  M. Gao, J. A. Fessler, and H.-P. Chan, IEEE Transactions on Medical Imaging, Vol. 40, No. 7, pp. 1805-1816, July 2021. Paper Supplement Code

Conference Proceedings and Abstracts

• Deep Convolutional Neural Network Regularized Digital Breast Tomosynthesis Reconstruction With Detector Blur and Correlated Noise Modeling

  M. Gao, J. A. Fessler, and H.-P. Chan, in Proceedings of SPIE, 12031, 1203108, 2022. Paper Slides

• Plug-and-play Reconstruction With Deep Learning Denoising for Improving Detectability of Microcalcifications in Digital Breast Tomosynthesis Images

  M. Gao, J. A. Fessler, and H.-P. Chan, in RSNA Scientific Assembly and Annual Meeting, 2021. Slides

• Digital Breast Tomosynthesis Denoising Using Deep Convolutional Neural Network: Effects of Dose Level of Training Target Images

  M. Gao, J. A. Fessler, and H.-P. Chan, in Proceedings of SPIE, 11595, 115951K, 2021. Paper Slides

• Training Deep Convolutional Neural Network With In Silico Data for Denoising Digital Breast Tomosynthesis Images

  M. Gao, J. A. Fessler, and H.-P. Chan, in RSNA Scientific Assembly and Annual Meeting, 2020. Slides

• Deep Convolutional Neural Network Denoising for Digital Breast Tomosynthesis Reconstruction

  M. Gao, R. K. Samala, J. A. Fessler, and H.-P. Chan, in Proceedings of SPIE, 11312, 113120Q, 2020. Paper Slides

• Myelin Water Fraction Estimation Using Small-tip Fast Recovery MRI

  S. T. Whitaker, G. Nataraj, M. Gao, J.-F. Nielsen, and J. A. Fessler, in Proceedings of ISMRM Annual Conference, 2019. Paper

• Kernel Regression for Fast Myelin Water Imaging

  G. Nataraj, M. Gao, J.-F. Nielsen, and J. A. Fessler, in ISMRM Workshop on Machine Learning Part II, 2018 (2nd-place poster award).

• Shallow Learning With Kernels for Dictionary-free Magnetic Resonance Fingerprinting

  G. Nataraj, M. Gao, J. Assländer, C. Scott, and J. A. Fessler, in ISMRM Workshop on MR Fingerprinting, 2017. Paper Slides