Classification of human epithelial type 2 cell images using independent component analysis

2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Volumn , Issue , 2013, Pages 733-737

  Yang, Yan ^a,b   Wiliem, Arnold ^a   Alavi, Azadeh ^a,b   Hobson, Peter ^c  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b CSIRO   (Australia)

^c SULLIVAN NICOLAIDES PATHOLOGY   (Australia)

Author keywords

Anti Nuclear Antibodies Pathology Test; Computer Aided Diagnostic; HEp 2 cells classification; Independent Component Analysis; Indirect Immunofluorescence

Indexed keywords

ANTIBODIES; AUTOMATION; CELLS; COLLAGEN; COMPUTER AIDED ANALYSIS; COMPUTER AIDED DIAGNOSIS; CYTOLOGY; FILTER BANKS; FLUORESCENCE; IMAGE CLASSIFICATION; INDEPENDENT COMPONENT ANALYSIS; MUSCULOSKELETAL SYSTEM; PATHOLOGY; SUPPORT VECTOR MACHINES;

AUTOMATED SYSTEMS; COMPUTER AIDED DIAGNOSTICS; COMPUTER VISION ALGORITHMS; CONNECTIVE TISSUE DISEASE; CORRELATION KERNEL; HEP-2 CELLS; INDEPENDENT COMPONENT ANALYSIS(ICA); INDIRECT IMMUNOFLUORESCENCE;

IMAGE ANALYSIS;

EID: 84897585846     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2013.6738151     Document Type: Conference Paper

References (14)

1. E. Cordelli and P. Soda, "Color to grayscale staining pattern representation in iif," in International Symposium on Computer-Based Medical Systems (CBMS), 2011, pp. 1-6.
2. P. Elbischger, S. Geerts, K. Sander, G. Ziervogel-Lukas, and P. Sinah, "Algorithmic framework for hep-2 fluorescence pattern classification to aid auto-immune diseases diagnosis," in Biomedical Imaging: From Nano to Macro, 2009, pp. 562-565.
3. P. Strandmark, J. Uĺen, and F. Kahl, "Hep-2 staining pattern classification," in International Conference Pattern Recognition, 2012, pp. 562-565.
4. R. Hiemann, T. B̈uttner, T. Krieger, D. Roggenbuck, U. Sack, and K. Conrad, "Challenges of automated screening and differentiation of non-organ specific autoantibodies on hep-2 cells," Autoimmunity Reviews, vol. 9, no. 1, pp. 17-22, 2009.
5. T. Hsieh, Y. Huang, C. Chung, and Y. Huang, "Hep-2 cell classification in indirect immunofluorescence images," in International Conference on Information, Communications and Signal Processing, 2009.
6. P. Soda and G. Iannello, "Aggregation of classifiers for staining pattern recognition in antinuclear autoantibodies analysis," IEEE Transactions on Information Technology in Biomedicine, vol. 13, no. 3, pp. 322-329, 2009.
7. I. Theodorakopoulos, D. Kastaniotis, G. Economou, and S. Fotopoulos, "Hep-2 cells classification via fusion of morphological and textural features," in IEEE 12th International Conference on Bioinformatics &Bioengineering, 2012, pp. 689-694.
8. A. Wiliem, Y. Wong, C. Sanderson, P. Hobson, S. Chen, and B. Lovell, "Classification of human epithelial type 2 cell indirect immunofluoresence images via codebook based descriptors," in IEEE Workshop on Applications of Computer Vision (WACV), January 2013.
9. B.A. Olshausen et al., "Emergence of simple-cell receptive field properties by learning a sparse code for natural images," Nature, vol. 381, no. 6583, pp. 607-609, 1996.
10. X. Hou and L. Zhang, "Dynamic visual attention: Searching for coding length increments," Advances in neural information processing systems, vol. 21, pp. 681-688, 2008.
11. C. Kanan and G. Cottrell, "Robust classification of objects, faces, and flowers using natural image statistics," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010, pp. 2472-2479.
12. A. Hyv̈arinen, J. Hurri, and P.O. Hoyer, Natural Image Statistics: A Probabilistic Approach to Early Computational Vision., vol. 39, Springer, 2009.
13. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2006, pp. 2169-2178.
14. H. Jiang andW.K. Ching, "Correlation kernels for support vector machines classification with applications in cancer data," Computational and Mathematical Methods in Medicine, 2012.