A texture-based methodology for identifying tissue type in magnetic resonance images

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Volumn , Issue , 2008, Pages 464-467

  Barnathan, Michael ^a   Zhang, Jingjing ^a   Miranda, Erickson ^a   Megalooikonomou, Vasileios ^a   Faro, Scott ^b   Hensley, Harvey ^c   Del Valle, Luis ^d   Khalili, Kamel ^d   Gordon, Jennifer ^d   Mohamed, Feroze B ^b  

^a Temple University   (United States)

^b TEMPLE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c FOX CHASE CANCER CENTER   (United States)

^d TEMPLE UNIVERSITY   (United States)

Author keywords

Brain images; Classification; Pattern analysis; Texture descriptors; Vector quantization

Indexed keywords

BRAIN MODELS; CLASSIFICATION (OF INFORMATION); COMPUTER NETWORKS; DECISION MAKING; DECISION THEORY; DECISION TREES; IMAGE COMPRESSION; IMAGE ENHANCEMENT; IMAGE RETRIEVAL; LEARNING SYSTEMS; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; NEURAL NETWORKS; PATHOLOGY; RESONANCE; SUPPORT VECTOR MACHINES; TECHNICAL PRESENTATIONS; TEXTURES; VECTORS;

BRAIN IMAGES; CLASSIFICATION; PATTERN ANALYSIS; TEXTURE DESCRIPTORS; VECTOR QUANTIZATION;

FEATURE EXTRACTION;

EID: 51049115744     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2008.4541033     Document Type: Conference Paper

References (8)

1. Kontos, D., Wang, Q., Megalooikonomou, V., Maurer, A. H., Knight, L. C., Kantor, S., Fisher, R. S., Simonian, H. P., Parkman, H. P., A tool for handling uncertainty in segmenting regions of interest in medical images, International Journal of Intelligent Systems Technologies, Special Issue on "Intelligent Image and Video Processing and Applications: The Role of Uncertainty", Vol. 1, Nos. 3/4, pp. 194-210, 2006.
2. Zhang, J., Megalooikonomou, V., An Effective and Efficient Technique for Searching for Similar Brain Activation Patterns, Proceedings of the IEEE International Symposium on Biomedical Imaging, Washington DC, Apr. 2007.
3. Wang, Q., Megalooikonomou, V., Kontos, D., A Medical Image Retrieval Framework, Proceedings of the 2005 IEEE International Workshop on Machine Learning for Signal Processing (MLSP05), Mystic, Connecticut, Sep. 2005.
4. Megalooikonomou, V., Kontos, D., Pokrajac, D., Lazarevic, A., Obradovic, Z., Boyko, O., Saykin, A., Ford, J., Makedon, F., Classification and Mining of Brain Image Data Using Adaptive Recursive Partitioning Methods: Application to Alzheimer Disease and Brain Activation Patterns, Presented at the Human Brain Mapping Conference (OHBM'03), New York, NY, Jun. 2003.
5. Krynska, B., Otte, J., Franks, R., Khalili, K., and Croul, S., Human ubiquitous JCV(CY) T-antigen gene induces brain tumors in experimental animals, Oncogene, Vol. 18 no. 1, pp. 39-46.
6. Mitra, S., Yang, S.Y., High Fidelity Adaptive Vector Quantization at Very Low Bit Rates for Progressive Transmission of Radiographic Images, Journal of Electronic Imaging, Vol. 8, pp.23-35, 1999.
7. Zhu L., Rao, A., Zhang, A., Advanced Feature Extraction for Keyblock-based Image Retrieval, Information Systems, Vol. 27 no. 8, pp. 537-557.
8. Bhattacharya, A., Ljosa, V., Pan, J., Verardo, M.R., Yang, H., Faloutsos, C., Singh, A.K., ViVo: Visual Vocabulary Construction for Mining Biomedical Images, Proceedings of the Fifth IEEE International Conference on Data Mining, Houston, TX, Nov. 2005.