A deep semantic mobile application for thyroid cytopathology

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 9789, Issue , 2016, Pages

  Kim, Edward ^a   Corte Real, Miguel ^a   Baloch, Zubair ^b  

^a Department of Computing Sciences and Center of Excellence in Enterprise Technology   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Convolutional neural networks; Cytology; Deep learning; Image retrieval; Machine learning; Mobile; Ontology; Semantic web; Thyroid

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONVOLUTION; CYTOLOGY; DIAGNOSIS; IMAGE RETRIEVAL; INFORMATION SCIENCE; LEARNING ALGORITHMS; LEARNING SYSTEMS; MOBILE COMPUTING; MOBILE TELECOMMUNICATION SYSTEMS; NEURAL NETWORKS; ONTOLOGY; PATHOLOGY; SEMANTIC WEB;

ANATOMICAL STRUCTURES; CONVOLUTIONAL NEURAL NETWORK; DEEP LEARNING; MACHINE LEARNING TECHNIQUES; MOBILE; MOBILE APPLICATIONS; MULTIMEDIA METADATA; THYROID;

MEDICAL IMAGING;

EID: 84976273604     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.2216468     Document Type: Conference Paper

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