Conference proceeding
Digital Pathology Annotation Data for Improved Deep Neural Network Classification
MEDICAL IMAGING 2017: IMAGING INFORMATICS FOR HEALTHCARE, RESEARCH, AND APPLICATIONS, v 10138, 101380
01 Jan 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In the field of digital pathology, there is an explosive amount of imaging data being generated. Thus, there is an ever growing need to create assistive or automatic methods to analyze collections of images for screening and classification. Machine learning, specifically deep learning algorithms, developed for digital pathology have the potential to assist in this way. Deep learning architectures have demonstrated great success over existing classification models but require massive amounts of labeled training data that either doesn't exist or are cost and time prohibitive to obtain. In this project, we present a framework for representing, collecting, validating, and utilizing cytopathology features for improved neural network classification.
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Details
- Title
- Digital Pathology Annotation Data for Improved Deep Neural Network Classification
- Creators
- Edward Kim - Villanova UniversitySaiLakshmiDeepika Mente - Villanova UniversityAndrew Keenan - Villanova UniversityVijay Gehlot - Villanova University
- Contributors
- Tessa S Cook (Editor) - Hospital of the University of PennsylvaniaJianguo Zhang (Editor) - Shanghai Institute of Technical Physics
- Publication Details
- MEDICAL IMAGING 2017: IMAGING INFORMATICS FOR HEALTHCARE, RESEARCH, AND APPLICATIONS, v 10138, 101380
- Conference
- Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications (Orlando, Florida, United States, 11 Feb 2017–16 Feb 2017)
- Series
- Proceedings of SPIE
- Publisher
- Spie-Int Soc Optical Engineering
- Number of pages
- 7
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000404178400011
- Scopus ID
- 2-s2.0-85020474024
- Other Identifier
- 991021884692104721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Optics
- Radiology, Nuclear Medicine & Medical Imaging