Matthew A. Barish
Orcid: 0000-0002-7521-8878Affiliations:
- Stony Brook University, NY, USA
According to our database1,
Matthew A. Barish
authored at least 18 papers
between 2010 and 2022.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2022
2021
External validation demonstrates limited clinical utility of the interpretable mortality prediction model for patients with COVID-19.
Nat. Mach. Intell., 2021
2020
3D-GLCM CNN: A 3-Dimensional Gray-Level Co-Occurrence Matrix-Based CNN Model for Polyp Classification via CT Colonography.
IEEE Trans. Medical Imaging, 2020
Integration of optical and virtual colonoscopy images for enhanced classification of colorectal polyps.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Vis. Comput. Ind. Biomed. Art, 2019
A statistical analysis of oral tagging in CT colonography and its impact on flat polyp detection and characterization.
Proceedings of the Medical Imaging 2019: Image Perception, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
2018
2017
IEEE Trans. Vis. Comput. Graph., 2017
A study of oral contrast coating on the surface of polyps: an implication for computer-aided detection and classification of polyps.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
2016
Texture Feature Extraction and Analysis for Polyp Differentiation via Computed Tomography Colonography.
IEEE Trans. Medical Imaging, 2016
Crowdsourcing for Identification of Polyp-Free Segments in Virtual Colonoscopy Videos.
CoRR, 2016
Maximal area and conformal welding heuristics for optimal slice selection in splenic volume estimation.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
2013
IEEE Trans. Biomed. Eng., 2013
2012
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012
2011
Proceedings of the Medical Imaging 2011: Visualization, 2011
2010
Projection-based features for reducing false positives in computer-aided detection of colonic polyps in CT colonography.
Proceedings of the Medical Imaging 2010: Computer-Aided Diagnosis, 2010