Matthew Sherman Brown
Professor-in-Residence, Radiological Sciences, University of California Los Angeles
UCLA Radiol Sci
924 Westwood Blvd., Ste 650
Los Angeles, CA 90095
After receiving his doctorate in Computer Science from the University of New South Wales in his native Australia, Dr. Matthew Brown joined the UCLA Department of Radiological Sciences in 1996 and is currently an Associate Professor. Dr. Brown has more than 15 years of R&D experience in quantitative medical image analysis in medicine, computer vision, and computer-aided diagnosis systems applied to clinical trials. As a computer scientist he has more than 20 years experience in software engineering, database administration and system validation. Dr. Brown’s research interests include the development of quantitative imaging biomarkers. Measurements are made using automated computer vision systems to increase accuracy and reproducibility. Machine learning and classification techniques are used for prediction or early assessment of treatment outcomes. Dr. Brown is part of the open source development team of Simple Mind: A virtual data scientist built using Cognitive AI. SimpleMind is an open source software framework that supports deep neural networks (DNNs) with higher level reasoning and automatic parameter tuning.
- Brown MS, Wong KP, Shrestha L, Wahi-Anwar M, Daly M, Foster G, Abtin F, Ruchalski KL, Goldin JG, Enzmann D. Automated Endotracheal Tube Placement Check Using Semantically Embedded Deep Neural Networks.. Academic radiology, 2022.
- Brown MS, Lo P, Goldin JG, Barnoy E, Kim GHJ, McNitt-Gray MF, Aberle DR. Correction to: Toward clinically usable CAD for lung cancer screening with computed tomography.. European radiology, 2020.
- Brown M, Browning P, Wahi-Anwar MW, Murphy M, Delgado J, Greenspan H, Abtin F, Ghahremani S, Yaghmai N, da Costa I, Becker M, Goldin J. Integration of Chest CT CAD into the Clinical Workflow and Impact on Radiologist Efficiency.. Academic radiology, 2018.
- Brown MS, Lo P, Goldin JG, Barnoy E, Kim GH, McNitt-Gray MF, Aberle DR. Toward clinically usable CAD for lung cancer screening with computed tomography.. European radiology, 2014.
- Brown MS, Chu GH, Kim HJ, Allen-Auerbach M, Poon C, Bridges J, Vidovic A, Ramakrishna B, Ho J, Morris MJ, Larson SM, Scher HI, Goldin JG. Computer-aided quantitative bone scan assessment of prostate cancer treatment response.. Nuclear medicine communications, 2012.
- Brown MS, Kim HJ, Abtin FG, Strange C, Galperin-Aizenberg M, Pais R, Da Costa IG, Ordookhani A, Chong D, Ni C, McNitt-Gray MF, Tashkin DP, Goldin JG. Emphysema lung lobe volume reduction: effects on the ipsilateral and contralateral lobes.. European radiology, 2012.
- Brown MS, Kim HJ, Abtin F, Da Costa I, Pais R, Ahmad S, Angel E, Ni C, Kleerup EC, Gjertson DW, McNitt-Gray MF, Goldin JG. Reproducibility of lung and lobar volume measurements using computed tomography.. Academic radiology, 2009.
- Brown MS, Pais R, Qing P, Shah S, McNitt-Gray MF, Goldin JG, Petkovska I, Tran L, Aberle DR. An architecture for computer-aided detection and radiologic measurement of lung nodules in clinical trials.. Cancer informatics, 2007.
- Brown MS, McNitt-Gray MF, Pais R, Shah SK, Qing P, Da Costa I, Aberle DR, Goldin JG. CAD in clinical trials: current role and architectural requirements.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 2007.
- Brown MS, Goldin JG, Rogers S, Kim HJ, Suh RD, McNitt-Gray MF, Shah SK, Truong D, Brown K, Sayre JW, Gjertson DW, Batra P, Aberle DR. Computer-aided lung nodule detection in CT: results of large-scale observer test.. Academic radiology, 2005.
- Brown MS, Shah SK, Pais RC, Lee YZ, McNitt-Gray MF, Goldin JG, Cardenas AF, Aberle DR. Database design and implementation for quantitative image analysis research.. IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society, 2005.
- Brown MS, Goldin JG, Suh RD, McNitt-Gray MF, Sayre JW, Aberle DR. Lung micronodules: automated method for detection at thin-section CT--initial experience.. Radiology, 2003.
- Brown MS, Feng WC, Hall TR, McNitt-Gray MF, Churchill BM. Knowledge-based segmentation of pediatric kidneys in CT for measurement of parenchymal volume.. Journal of computer assisted tomography, 2001.