Mark A. Anastasio
Scholar

Mark A. Anastasio

Google Scholar ID: Ws3UU-AAAAAJ
University of Illinois Urbana-Champaign
Image reconstructionimaging sciencemachine learning for imagingphotoacoustic tomography
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Citations & Impact
All-time
Citations
5,793
 
H-index
41
 
i10-index
136
 
Publications
20
 
Co-authors
0
 
Contact
Emailmaa@illinois.eduTwitterOpen ↗
Publications
4 items
A Learning-based Framework for Spatial Impulse Response Compensation in 3D Photoacoustic Computed Tomography.
arXiv.org · 2026
Cited
0
Benchmarking Deep Learning-Based Reconstruction Methods for Photoacoustic Computed Tomography with Clinically Relevant Synthetic Datasets.
arXiv.org · 2026
Cited
0
Application of a Virtual Imaging Framework for Investigating a Deep Learning-Based Reconstruction Method for 3D Quantitative Photoacoustic Computed Tomography
2025
Cited
0
Physics and Deep Learning in Computational Wave Imaging
arXiv.org · 2024
Cited
1
Resume (English only)
Academic Achievements
  • - Paper accepted to IEEE Transactions on Medical Imaging
  • - Selected as a 2025 McGinnis Medical Innovation Graduate Fellow
  • - Presented at SPIE-MI and SPIE Photonics West
  • - Paper accepted by Inverse Problems
Research Experience
  • - Research focuses on computational inverse problems in imaging
  • - Development of tomographic image reconstruction methods
  • - Use of deep learning for objective image quality assessment
  • - Development of machine learning methods for imaging applications
Background
  • Research interests include computational image science, development of tomographic image reconstruction methods, and the application of machine learning in imaging.
Miscellany
  • The laboratory is directed by Professor Mark Anastasio and funded by the National Institute of Health and the National Science Foundation.
Co-authors
0 total
Co-authors: 0 (list not available)