CONFERENCE PROCEEDINGS
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Charlems Alvarez Jimenez
at Case Western Reserve Univ
SPIE Involvement:
Author
Publications (5)
Proceedings Article | 21 December 2018 Paper
Extracting multiscale patterns for classification of non-small cell lung cancer in CT images
Proceedings Volume 10975, 109750F (2018) https://doi.org/10.1117/12.2513347
KEYWORDS: Tumors, Lung cancer, Computed tomography, Lung, Image classification, Binary data, Image segmentation, Tissues, Cancer, X-ray computed tomography
Proceedings Article | 17 November 2017 Paper
Gaussian mixture models for detection of autism spectrum disorders (ASD) in magnetic resonance imaging
Proceedings Volume 10572, 105720F (2017) https://doi.org/10.1117/12.2285902
KEYWORDS: Brain, Magnetic resonance imaging, Image segmentation, Neuroimaging, Expectation maximization algorithms, Databases, Image registration, Binary data, Diagnostics, Analytical research
Proceedings Article | 22 December 2015 Paper
A characterization of Parkinson's disease by describing the visual field motion during gait
David Trujillo, Fabio Martínez, Angélica Atehortúa, Charlens Alvarez, Eduardo Romero
Proceedings Volume 9681, 96810K (2015) https://doi.org/10.1117/12.2211438
KEYWORDS: Gait analysis, Eye, Parkinson's disease, Optical flow, Visualization, Pathology, Motion analysis, Optical tracking, Motion controllers, Medical imaging
Proceedings Article | 28 January 2015 Paper
An automatic multi-atlas prostate segmentation in MRI using a multiscale representation and a label fusion strategy
Charlens Álvarez, Fabio Martínez, Eduardo Romero
Proceedings Volume 9287, 92870D (2015) https://doi.org/10.1117/12.2073449
KEYWORDS: Prostate, Image segmentation, Magnetic resonance imaging, Image fusion, Radiotherapy, Multiscale representation, Prostate cancer, Databases, Statistical analysis, Magnetism
Proceedings Article | 19 November 2013 Paper
A novel atlas-based approach for MRI prostate segmentation using multiscale points of interest
Charlens Álvarez, Fabio Martínez, Eduardo Romero
Proceedings Volume 8922, 89220O (2013) https://doi.org/10.1117/12.2035462
KEYWORDS: Magnetic resonance imaging, Prostate, Image segmentation, Radiotherapy, Tissues, Databases, Computed tomography, Shape analysis, Neodymium, Prostate cancer
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