I have established my career through the development and evaluation of computerized techniques for the quantitative analysis of medical images and the assessment of tumor response to therapy. More specifically, my research has involved the computerized detection and evaluation of lung nodules in thoracic computed tomography (CT) scans, the assessment of image quality and pathologic change in temporally subtracted chest radiographic images, the computerized evaluation of mesothelioma tumor and response to therapy in CT scans, critical analyses of image-based tumor response assessment for mesothelioma, the development of objective CT-based metrics for the quantification of mucosal inflammation due to sinusitis, the application of radiomics to the pre- and post-treatment CT scans of radiation therapy patients to predict normal lung tissue complications, and the evaluation of reference standards for computer-aided diagnosis (CAD) research. As the local principal investigator for the Lung Image Database Consortium project that spanned 10 years and as the faculty director of the University of Chicago’s Human Imaging Research Office, I have extensive experience with interdisciplinary and multi-institutional image-based projects.
The University of Chicago
Chicago, IL
Ph.D. - Medical Physics
1997
The University of Chicago
Chicago, IL
B.A. - Physics
1987
MIDRC mRALE Mastermind Grand Challenge: AI to predict COVID severity on chest radiographs.
MIDRC mRALE Mastermind Grand Challenge: AI to predict COVID severity on chest radiographs. J Med Imaging (Bellingham). 2025 Mar; 12(2):024505.
PMID: 40276098
Impact of retraining and data partitions on the generalizability of a deep learning model in the task of COVID-19 classification on chest radiographs.
Impact of retraining and data partitions on the generalizability of a deep learning model in the task of COVID-19 classification on chest radiographs. J Med Imaging (Bellingham). 2024 Nov; 11(6):064503.
PMID: 39734609
Radiomics for differentiation of somatic BAP1 mutation on CT scans of patients with pleural mesothelioma.
Radiomics for differentiation of somatic BAP1 mutation on CT scans of patients with pleural mesothelioma. J Med Imaging (Bellingham). 2024 Nov; 11(6):064501.
PMID: 39669009
Imaging in pleural Mesothelioma: A review of the 16th International Conference of the International Mesothelioma Interest Group.
Imaging in pleural Mesothelioma: A review of the 16th International Conference of the International Mesothelioma Interest Group. Lung Cancer. 2024 Jul; 193:107832.
PMID: 38875938
AI and machine learning in medical imaging: key points from development to translation.
AI and machine learning in medical imaging: key points from development to translation. BJR Artif Intell. 2024 Jan; 1(1):ubae006.
PMID: 38828430
Implementation of a high-resolution, high-contrast magnetic resonance imaging protocol with extended delayed phases for peritoneal mesothelioma.
Implementation of a high-resolution, high-contrast magnetic resonance imaging protocol with extended delayed phases for peritoneal mesothelioma. Quant Imaging Med Surg. 2024 Mar 15; 14(3):2580-2589.
PMID: 38545076
Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing.
Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing. BJR Artif Intell. 2024 Jan; 1(1):ubae003.
PMID: 38476957
Assessment of a deep learning model for COVID-19 classification on chest radiographs: a comparison across image acquisition techniques and clinical factors.
Assessment of a deep learning model for COVID-19 classification on chest radiographs: a comparison across image acquisition techniques and clinical factors. J Med Imaging (Bellingham). 2023 Nov; 10(6):064504.
PMID: 38162317
Magnetic resonance imaging preprocessing and radiomic features for classification of autosomal dominant polycystic kidney disease genotype.
Magnetic resonance imaging preprocessing and radiomic features for classification of autosomal dominant polycystic kidney disease genotype. J Med Imaging (Bellingham). 2023 Nov; 10(6):064503.
PMID: 38156331
Convolutional Neural Networks for Segmentation of Malignant Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).
Convolutional Neural Networks for Segmentation of Malignant Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance). ArXiv. 2023 Nov 30.
PMID: 38076518
iMig Advancement Award
International Mesothelioma Interest Group
2021
Fellow
Society of Photo-Optical Instrumentation Engineers (SPIE)
2018
Distinguished Investigator
Academy of Radiology Research
2016
Fellow
American Association of Physicists in Medicine
2014
Kurt Rossmann Award for Excellence in Medical Physics Teaching
The University of Chicago
2012
Raine Visiting Professor
University of Western Australia
2009
Kurt Rossmann Award for Excellence in Medical Physics Teaching
The University of Chicago
2002