Ontology-guided organ detection to retrieve web images of disease manifestation: Towards the construction of a consumer-based health image library

Journal of the American Medical Informatics Association

Volumn 20, Issue 6, 2013, Pages 1076-1081

  Chen, Yang ^a   Ren, Xiaofeng ^b   Zhang, Guo Qiang ^a,c   Xu, Rong ^c  

^a CASE WESTERN RESERVE UNIVERSITY   (United States)

^b INTEL CORPORATION   (United States)

^c CASE WESTERN RESERVE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; BODY REGIONS; DATA BASE; EAR; HAND; IMAGE RETRIEVAL; INTERNET; LIP; MEDICAL INFORMATION SYSTEM; PATIENT EDUCATION; SELF CARE; UNIFIED MEDICAL LANGUAGE SYSTEM; VISUAL INFORMATION;

IMAGE RETRIEVAL; OBJECT DETECTION; ONTOLOGY;

CONSUMER HEALTH INFORMATION; DISEASE; FOOT; HAND; HEAD; HUMANS; INFORMATION STORAGE AND RETRIEVAL; INTERNET; PHOTOGRAPHY; UNIFIED MEDICAL LANGUAGE SYSTEM;

EID: 84886284263     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2012-001380     Document Type: Article

References (22)

1. Lindberg D, Humphreys B, McCray A. The unified medical language system. Methods Inf Med 1993;32:281-91.
2. Armato S III, McLennan G, McNitt-Gray M, et al. Lung image database consortium: developing a resource for the medical imaging research community. Radiology 2004;232:739-48.
3. Keator D, Grethe J, Marcus D, et al. A national human neuroimaging collaboratory enabled by the biomedical informatics research network (birn). IEEE Trans Inf Tech in Biomed 2008;12:162-72.
4. A.D.A.M. http://www.adam.com/ (accessed Sept 2012).
5. Rosse C, Mejino J. A reference ontology for bioinformatics: the foundational model of anatomy. J Biomed Inform 2003;36:478-500.
6. ICD-9-CM: international classification of diseases, 9th revision; clinical modification, 6th edition, 2006
7. Liu S, Wei M, Moore R, et al. Rxnorm: prescription for electronic drug information exchange. IT Professional 2005;7:17-23.
8. Datta R, Joshi D, Li J, et al. Image retrieval: Ideas, influences, and trends of the new age. ACM Comput Surv 2008;40:1-60.
9. Chapelle O, Haffner P, Vapnik VH. Support vector machines for histogram-based image classification. IEEE Trans Neural Networks 1999;10:1055-64.
10. Panda N, Chang EY. Efficient top-k hyperplane query processing for multimedia information retrieval. ACM International Conference of Multimedia; Santa Barbara, CA, USA. 2006;317-26.
11. Li J, Wang JZ. Real-time computerized annotation of pictures. IEEE Trans Pattern Anal Mach Intell 2008;30:985-1002.
12. Feng H, Shi R, Chua TS. A bootstrapping framework for annotating and retrieving www images. ACM International Conference of Multimedia; New York, NY, USA. 2004;960-7.
13. Tong S, Chang E. Support vector machine active learning for image retrieval. The Ninth ACM International Conference on Multimedia; Ottawa, Ontario, Canada. 2001;107-18.
14. Deserno TM, Antani S, Long RL. Content-based image retrieval for scientific literature access. Methods Inf Med 2009;48:371-80.
15. Muller H, Herrera A, Kalpathy-Cramer J, et al. Overview of the ImageCLEF 2012 medical image retrieval and classification tasks. CLEF 2012 Evaluation Labs and Workshop, Online Working Notes; Rome, Italy, 17-20 September 2012.
16. Simpson MS, You D, Rahman MM, et al. Towards the creation of a visual ontology of biomedical imaging entities. AMIA Annual Symposium proceedings; Chicago, Illinois, USA. 2012;866-75.
17. Deng J, Berg A, Fei-Fei L. Hierarchical semantic indexing for large scale image retrieval. IEEE Computer Vision and Pattern Recognition (CVPR); Colorado Springs, CO, USA.2011;785-92.
18. Chen Y, Zhang G, Xu R. Semi-supervised image classification for automatic construction of a health image library. ACM SIGHIT International Health Informatics Symposium; Miami, Florida, USA. 2012;111-20.
19. Lowe D. Object recognition from local scale-invariant features. International Conference on Computer Vision; Kerkyra, Corfu, Greece. 1999; 1150-7.
20. Dalal N, Triggs B. Histograms of oriented gradients for human detection. IEEE Computer Vision and Pattern Recognition (CVPR); Miami, FL, USA. 2009;1:886-93.
21. Zhang J, Marszalek M, Lazebnik S, et al. Local features and kernels for classification of texture and object categories: a comprehensive study. Int J Computer Vision 2007;73:213-38.
22. Felzenszwalb P, Girshick R, McAllester D, et al. Object detection with discriminatively trained part based models. IEEE Trans Pattern Anal Mach Intell 2010;32:1627-45.