Dr. James M. Brown Profile

Dr. James M. Brown

Research fellow at University of Lincoln

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Publications (4)

Proceedings Article | 13 March 2019 Presentation + Paper

Improved interpretability for computer-aided severity assessment of retinopathy of prematurity

Mara Graziani, James Brown, Vincent Andrearczyk, Veysi Yildiz, J. Peter Campbell, Deniz Erdogmus, Stratis Ioannidis, Michael Chiang, Jayashree Kalpathy-Cramer, Henning Müller

Proceedings Volume 10950, 109501R (2019) https://doi.org/10.1117/12.2512584

KEYWORDS: Visualization, Image segmentation, Feature extraction, Machine learning, Neurons, Network architectures, Diagnostics, Convolutional neural networks, Visual process modeling, Computer aided diagnosis and therapy

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Proceedings Article | 9 March 2018 Paper

Anatomical DCE-MRI phantoms generated from glioma patient data

Andrew Beers, Ken Chang, James Brown, Xia Zhu, Dipanjan Sengupta, Theodore Willke, Elizabeth Gerstner, Bruce Rosen, Jayashree Kalpathy-Cramer

Proceedings Volume 10573, 105732V (2018) https://doi.org/10.1117/12.2294961

KEYWORDS: Data modeling, Tissues, Magnetic resonance imaging, Head, Tumor growth modeling, Temporal resolution, Scanners, Motion models, Tumors, Data centers

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Proceedings Article | 6 March 2018 Presentation + Paper

Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning

James Brown, J. Peter Campbell, Andrew Beers, Ken Chang, Kyra Donohue, Susan Ostmo, R. V. Paul Chan, Jennifer Dy, Deniz Erdogmus, Stratis Ioannidis, Michael Chiang, Jayashree Kalpathy-Cramer

Proceedings Volume 10579, 105790Q (2018) https://doi.org/10.1117/12.2295942

KEYWORDS: Image segmentation, Visualization, Eye, Data centers, Ophthalmology, Machine learning, Convolutional neural networks, Health informatics

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Proceedings Article | 2 March 2018 Paper

Sequential neural networks for biologically informed glioma segmentation

Andrew Beers, Ken Chang, James Brown, Elizabeth Gerstner, Bruce Rosen, Jayashree Kalpathy-Cramer

Proceedings Volume 10574, 1057433 (2018) https://doi.org/10.1117/12.2293941

KEYWORDS: Tumors, Image segmentation, Neural networks, Magnetic resonance imaging, Tissues, Brain, Clinical trials, Biomedical optics, Detection and tracking algorithms, Data modeling

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