Thomas J. Re

Evaluating deep learning methods in detecting and segmenting different sizes of brain metastases on 3D post-contrast T1-weighted images

Eli Gibson, James M. Balter, Yue Cao, 2021, Journal of medical imaging.

Brain midline shift detection and quantification by a cascaded deep network pipeline on non-contrast computed tomography scans

Dorin Comaniciu, Eli Gibson, Filiz Bunyak, 2021, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT

Dorin Comaniciu, Thomas Flohr, Zhoubing Xu, 2020, Radiology. Artificial intelligence.

Machine learning automatically detects COVID-19 using chest CTs in a large multicenter cohort

Dorin Comaniciu, Thomas Flohr, Sasa Grbic, 2020, European Radiology.

Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings

Thomas J. Re, D. Comaniciu, G. Sommer, 2021, Korean journal of radiology.

3D Tomographic Pattern Synthesis for Enhancing the Quantification of COVID-19 pdf

Youngjin Yoo, Zhoubing Xu, Sasa Grbic, 2020, ArXiv.

Automated detection of critical findings in multi-parametric brain MRI using a system of 3D neural networks

Thomas J. Re, D. Comaniciu, H. Meyer, 2021, Scientific Reports.

Artificial Intelligence with Statistical Confidence Scores for Detection of Acute or Subacute Hemorrhage on Noncontrast CT Head Scans.

Thomas J. Re, D. Comaniciu, Y. Lui, 2022, Radiology. Artificial intelligence.

3D-2D GAN based brain metastasis synthesis with configurable parameters for fully 3D data augmentation

Thomas J. Re, D. Kondziolka, D. Comaniciu, 2023, Medical Imaging.

Quantification of Tomographic Patterns associated with COVID-19 from Chest CT

Thomas J. Re, P. Grenier, D. Comaniciu, 2020, ArXiv.