Zhiyun Xue
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Zhiyun Xue has a total of 15 co-authors. Here are the top co-authors by number of shared publications:
- Sameer Antani
National Library of Medicine, National Institutes of Health, Bethesda, USA
5 shared publications - George R. Thoma
National Library of Medicine (United States)
4 shared publications L. Rodney Long
National Library of Medicine, National Institutes of Health (United States)
3 shared publications- Daekeun You
Lister Hill National Center for Biomedical Communications National Library of Medicine 8600 Rockville Pike, Bethesda MD 20894 USA
1 shared publication - Daniel Lopresti
Department of Computer Science and Engineering, Lehigh University, Bethlehem, USA
1 shared publication - Dina Demner-Fushman
Division of Intramural Research National Library of Medicine National Institutes of Health Bethesda MD USA
1 shared publication
Latest Publications
- 13 March 2017
- Published by SPIE-Intl Soc Optical Eng
- p. 1013807-1013807-9
Automatic multi-label annotation of abdominal CT images using CBIR
- 13 March 2017
- Published by SPIE-Intl Soc Optical Eng
- p. 1013807-1013807-9
Automatic multi-label annotation of abdominal CT images using CBIR
- 28 March 2013
- Published by Wiley in Journal of the American Society for Information Science and Technology
- Vol. 64 (5) , 893-908
Image retrieval from scientific publications: Text and image content processing to separate multipanel figures
- 28 March 2013
- Published by Wiley in Journal of the American Society for Information Science and Technology
- Vol. 64 (5) , 893-908
Image retrieval from scientific publications: Text and image content processing to separate multipanel figures
- 26 May 2010
- Published by Elsevier in Computerized Medical Imaging and Graphics
- Vol. 34 (8) , 593-604
A unified set of analysis tools for uterine cervix image segmentation
- 26 May 2010
- Published by Elsevier in Computerized Medical Imaging and Graphics
- Vol. 34 (8) , 593-604
A unified set of analysis tools for uterine cervix image segmentation
- 28 May 2008
- Published by Springer Nature in Journal of Signal Processing Systems
- Vol. 55 (1) , 185-207
Balancing the Role of Priors in Multi-Observer Segmentation Evaluation
- 28 May 2008
- Published by Springer Nature in Journal of Signal Processing Systems
- Vol. 55 (1) , 185-207
Balancing the Role of Priors in Multi-Observer Segmentation Evaluation
- 6 March 2008
- Published by SPIE-Intl Soc Optical Eng
- Vol. 6919, 691907
A web-accessible content-based cervicographic image retrieval system
Content-based image retrieval (CBIR) is the process of retrieving images by directly using image visual characteristics. In this paper, we present a prototype system implemented for CBIR for a uterine cervix image (cervigram) database. This cervigram database is a part of data collected in a multi-year longitudinal effort by the National Cancer Institute (NCI), and archived by the National Library of Medicine (NLM), for the study of the origins of, and factors related to, cervical precancer/cancer. Users may access the system with any Web browser. The system is built with a distributed architecture which is modular and expandable; the user interface is decoupled from the core indexing and retrieving algorithms, and uses open communication standards and open source software. The system tries to bridge the gap between a user's semantic understanding and image feature representation, by incorporating the user's knowledge. Given a user-specified query region, the system returns the most similar regions from the database, with respect to attributes of color, texture, and size. Experimental evaluation of the retrieval performance of the system on "groundtruth" test data illustrates its feasibility to serve as a possible research tool to aid the study of the visual characteristics of cervical neoplasia.
- 6 March 2008
- Published by SPIE-Intl Soc Optical Eng
- Vol. 6919, 691907
A web-accessible content-based cervicographic image retrieval system
Content-based image retrieval (CBIR) is the process of retrieving images by directly using image visual characteristics. In this paper, we present a prototype system implemented for CBIR for a uterine cervix image (cervigram) database. This cervigram database is a part of data collected in a multi-year longitudinal effort by the National Cancer Institute (NCI), and archived by the National Library of Medicine (NLM), for the study of the origins of, and factors related to, cervical precancer/cancer. Users may access the system with any Web browser. The system is built with a distributed architecture which is modular and expandable; the user interface is decoupled from the core indexing and retrieving algorithms, and uses open communication standards and open source software. The system tries to bridge the gap between a user's semantic understanding and image feature representation, by incorporating the user's knowledge. Given a user-specified query region, the system returns the most similar regions from the database, with respect to attributes of color, texture, and size. Experimental evaluation of the retrieval performance of the system on "groundtruth" test data illustrates its feasibility to serve as a possible research tool to aid the study of the visual characteristics of cervical neoplasia.