Feature-wise representation for both still and motion 3D medical images

Conference paper

Gao, X. 2014. Feature-wise representation for both still and motion 3D medical images. 2014 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI). San Diego, USA 06 - 09 Apr 2014 IEEE. pp. 1-4 https://doi.org/10.1109/SSIAI.2014.6806014
TypeConference paper
TitleFeature-wise representation for both still and motion 3D medical images
AuthorsGao, X.
Abstract

With the arrival of the state of the art medical imaging equipment, a plethora of images are acquired not only in higher dimensions (3D+) but also with various presenting forms of either still or motion, complicating data management systems even further. This paper offers, from an application point of view, representations of content features from both still 3D MR brain images and 3D ultrasound cardiac video sequences by demonstrating a developed online content-based image retrieval system, MIRAGE. The approaches of 3D SIFT coupled with sparse code have been appointed to facilitate the representation of image features, whereas widely applied four texture based approaches are also implemented to allow users’ benefit of different retrieving intentions.

KeywordsImaging; representing biomedical knowledge; multimedia image retrieval
Research GroupArtificial Intelligence group
Conference2014 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI)
Page range1-4
Proceedings Title2014 Southwest Symposium on Image Analysis and Interpretation
SeriesProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
ISSN1550-5782
ISBN
Electronic9781479940530
PublisherIEEE
Publication dates
Print06 Apr 2014
Online01 May 2014
Publication process dates
Deposited16 May 2014
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1109/SSIAI.2014.6806014
Scopus EID2-s2.0-84902265044
Web of Science identifierWOS:000355255900001
LanguageEnglish
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Detection of head motions using a vision model
Gao, X., Shaposhnikov, D., Podladchikova, L., Batty, S. and Clark, J. 2007. Detection of head motions using a vision model. Bashshur, R. (ed.) 3rd IASTED International Conference on Telehealth. Montreal, QC, Canada 31 May - 01 Jun 2007 Anaheim, CA Acta Press. pp. 167-171
Recognition of traffic signs based on their colour and shape features extracted using human vision models
Gao, X., Podladchikova, L., Shaposhnikov, D., Hong, K. and Shevtsova, N. 2006. Recognition of traffic signs based on their colour and shape features extracted using human vision models. Journal of Visual Communication and Image Representation. 17 (4), pp. 675-685. https://doi.org/10.1016/j.jvcir.2005.10.003
Colour management in telemedicine
Gao, X. 2004. Colour management in telemedicine. Hamza, M. (ed.) 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 Anaheim, CA Acta Press. pp. 361-364
Application of vision models to traffic sign recognition
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2004. Application of vision models to traffic sign recognition. Kaynak, O., Alpaydin, E., Oja, E. and Xu, L. (ed.) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. Istanbul, Turkey 26 - 29 Sep 2003 Berlin, Heidelberg Springer. https://doi.org/10.1007/3-540-44989-2_131
Towards content-based retrieval for wallpaper images
Qian, Y., Tully, C., Hendon, Z. and Gao, X. 2003. Towards content-based retrieval for wallpaper images. 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 pp. 305-309
Vision models based identification of traffic signs
Gao, X., Podladchikova, L., Shaposhnikov, D., Shevtsova, N., Hong, K., Batty, S., Golovan, A. and Gusakova, V. 2002. Vision models based identification of traffic signs. 1st European Conference on Colour Graphics, Imaging, and Vision. University of Poitiers, France 02 - 05 Apr 2002 Society for Imaging Science and Technology.
Content based retrieval of lesioned brain images
Batty, S., Blandford, A., Clark, J., Fryer, T. and Gao, X. 2002. Content based retrieval of lesioned brain images. Siegel, E. and Huang, H. (ed.) SPIE Medical Imaging 2002. San Diego, California, United States 23 - 28 Feb 2002 Bellingham Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.466997
A method of vessel tracking for vessel diameter measurement on retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2001. A method of vessel tracking for vessel diameter measurement on retinal images. 2001 International Conference on Image Processing. Thessaloniki, Greece 07 - 10 Oct 2001 IEEE.
Computer algorithms for the automated measurement of retinal arteriolar diameters
Chapman, N., Witt, N., Gao, X., Bharath, A., Stanton, A., Thom, S. and Hughes, A. 2001. Computer algorithms for the automated measurement of retinal arteriolar diameters. British Journal of Ophthalmology. 85 (1), pp. 74-79. https://doi.org/10.1136/bjo.85.1.74
Quantification and characterization of arteries in retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2000. Quantification and characterization of arteries in retinal images. Computer Methods and Programs in Biomedicine. 63 (2), pp. 133-146. https://doi.org/10.1016/S0169-2607(00)00082-1