HEp-2 image classification using intensity order pooling based features and bag of words

Pattern Recognition

Volumn 47, Issue 7, 2014, Pages 2419-2427

  Shen, Linlin ^a   Lin, Jiaming ^a   Wu, Shengyin ^a   Yu, Shiqi ^a  

^a SHENZHEN UNIVERSITY   (China)

Author keywords

Bag of words; HEp 2 cell classification; Intensity order pooling

Indexed keywords

CLASSIFICATION (OF INFORMATION);

AUTOIMMUNE DISORDER; BAG OF WORDS; CELL CLASSIFICATION; FLUORESCENCE MICROSCOPES; GRADIENT FEATURE; HUMAN EPITHELIAL TYPE 2 CELL CLASSIFICATION; IMAGES CLASSIFICATION; INTENSITY ORDER POOLING; LABOUR-INTENSIVE; TRADITIONAL APPROACHES;

IMAGE CLASSIFICATION;

EID: 84897111309     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2013.09.020     Document Type: Article

References (24)

1. P. Perner, H. Perner, and B. Muller Mining knowledge for HEp-2 cell image classification Artificial Intelligence in Medicine 26 2002 161 173
2. U. Sack, S. Knoechner, H. Warschkau, U. Pigla, F. Emmrich, and M. Kamprad Computer-assisted classification of HEp-2 immunofluorescence patterns in autoimmune diagnostics Autoimmunity Reviews 2 2003 298 304
3. P. Soda, and G. Iannello Aggregation of classifiers for staining pattern recognition in antinuclear autoantibodies analysis IEEE Transactions on Information Technology in Biomedicine 13 2009 322 329
4. P. Foggia, G. Percannella, P. Soda, M. Vento, Early experiences in mitotic cells recognition on HEp-2 slides, in: Proceedings of the XXIII International Symposium on Computer-Based Medical Systems, 2010, pp. 38-43.
5. E. Cordelli, P. Soda, Methods for greyscale representation of HEp-2 colour images, in: Proceedings of the 23rd International Symposium on Computer-Based Medical Systems, 2010, pp. 383-388.
6. E. Cordelli, P. Soda, Color to grayscale staining pattern representation in IIF, in: Proceedings of the 24th International Symposium on Computer-Based Medical Systems, 2011, pp. 1-6.
7. G. Percannella, P. Foggia, P. Soda, Contest on HEp-2 cells classification, 2012.
8. K. Li, J. Yin, X. Kong, R. Zhang, W. Liu, Multiclass boosting SVM using different texture features in HEp-2 cell staining pattern classifiation, in: Proceedings of the 21st International Conference on Pattern Recognition, 2012, pp. 170-173.
9. S. Ghosh, V. Chaudhary, Feature analysis for automatic classifiation of HEp-2 florescence patterns: computer-aided diagnosis of auto-immune diseases, in: Proceedings of the 21st International Conference on Pattern Recognition, 2012, pp. 174-177.
10. P. Strandmark, U. Johannes, F. Kahl, HEp-2 staining pattern classification, in: Proceedings of the 21st International Conference on Pattern Recognition, 2012, pp. 33-36.
11. G. Thibault, J. Angulo, Efficient statistical-morphological cell texture characterization and characterization, in: Proceedings of the 21st International Conference on Pattern Recognition, 2012, pp. 2440-2443.
12. V. Snell, W. Christmas, J. Kittler, Texture and shape in fluorescence pattern identifiation for auto-immune disease diagnosis, in: Proceedings of the 21st International Conference on Pattern Recognition, 2012, pp. 3750-3753.
13. P. Foggia, G. Percannella, P. Soda, and M. Vento Benchmarking HEp-2 cells classification methods IEEE Transactions on Medical Imaging 32 2013 1878 1889
14. G. Iannello, L. Onofri, P. Soda, A bag of visual words approach for centromere and cytoplasmic staining pattern classification on HEp-2 images, in: Proceedings of the 25th International Symposium on Computer-Based Medical Systems, 2012, pp. 1-6.
15. G. Csurka, C.R. Dance, L. Fan, J. Willamowski, C. Bray, Visual Categorization with Bags of Keypoints, in Workshop on Statistical Learning in Computer Vision, ECCV, 2004, pp. 1-22.
16. B. Fan, F. Wu, and Z. Hu Rotationally invariant descriptors using intensity order pooling IEEE Transactions on Pattern Analysis and Machine Intelligence 34 2012 2031 2045
17. S. Lazebnik, C. Schmid, J. Ponce, Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories, in: Proceedings of the 19th IEEE Conference on Computer Vision and Pattern Recognition, 2006, pp. 2169-2178.
18. D. Sculley, Web-scale k-means clustering, in: Proceedings of the 19th international conference on World wide web, 2010, pp. 1177-1178.
19. Scikit Learn Toolbox. 〈 http://scikit-learn.org/ 〉
20. J. Philbin, O. Chum, M. Isard, J. Sivic, A. Zisserman, Lost in quantization: improving particular object retrieval in large scale image databases, in: Proceedings of the 22nd IEEE Conference on Computer Vision and Pattern Recognition, 2009, pp. 1-8.
21. J. Yang, K. Yu, Y. Gong, T. Huang, Linear spatial pyramid matching using sparse coding for image classification, in: Proceedings of the 22nd IEEE Conference on Computer Vision and Pattern Recognition, 2009, pp. 1794-1801.
22. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, Y Gong. Locality-constrained Linear Coding for image classification, in: Proceedings of the 23rd IEEE Conference on Computer Vision and Pattern Recognition, 2010, pp. 3360-3367.
23. Y-Lan Boureau, Nicolas Le Roux, Francis Bach, Jean Ponce, Yann LeCun, Ask the locals: multi-way local pooling for image recognition, in: Proceedings of the 24th IEEE International Conference on Computer Vision, 2011, pp. 2651-2658.
24. Bernhard E. Boser, Isabelle M. Guyon, Vladimir N. Vapnik, A training algorithm for optimal margin classifiers, in: Proceedings of the 5th ACM Annual Workshop on Computational Learning Theory, 1992, pp. 144-152.