COMPARATIVE STUDY OF DESCRIPTORS FOR MEDICAL IMAGE RETRIEVAL
Abstract
This paper presents results of comparative analysis of image descriptors in the context of content- based medical image retrieval problem. Experiments are carried out on 11 test databases using 137 different types of descriptors. Image descriptors based on co-occurrence matrices and local binary patterns showed the best performance.
References
1. Partik, B. Digital (R) Evolution in Radiology / B. Partik, C. Schaefer-Prokop // Digital radiology in chest imaging. – Springer Vienna, 2001. – P. 189–203.
2. Quality of DICOM header information for image categorization / M.O. Guld [et al.] // Medical Imaging 2002. International Society for Optics and Photonics. – San Diego, 2002. – P. 280–287.
3. Deselaers, T. Features for image retrieval: an experimental comparison / T. Deselaers, D. Keysers, H. Ney // Information Retrieval. – 2008. – Vol. 11, № 2. – P. 77–107.
4. Müller, H. The truth about Corel-evaluation in image retrieval / H. Müller, S. Marchand- Maillet, T. Pun // Image and Video Retrieval. – Springer Berlin Heidelberg, 2002. – P. 38–49.
5. ImageCLEF – The CLEF Cross Language Image Retrieval Track [Electronic resource]. – 2015. – Mode of access : http://www.imageclef.org. – Date of access : 15.05.2015.
6. Pattern Analysis, Statistical Modelling and Computational Learning [Electronic resource]. – 2015. – Mode of access : http://www.pascal-network.org. – Date of access : 15.05.2015.
7. Brodatz, P. Textures: A Photographic Album for Artists and Designers / P. Brodatz. – N.Y. : Dover Publications, 1966. – 112 p.
8. Brodatz texture database with CASIA V3 Iris database naming scheme [Electronic resource]. – 2012. – Mode of access : http://staff.neu.edu.tr/~kkilic/prj/lac/brodatz/brodatz.html. – Date of access : 11.01.2015.
9. Columbia University Image Library (COIL-20) [Electronic resource]. – 2013. – Mode of access : http://www.cs.columbia.edu/CAVE/software/softlib/coil-20.php. – Date of access : 01.06.2015.
10. Geometric features of Pollen grains [Electronic resource]. – 2013. – Mode of access : http://ome.grc.nia.nih.gov/iicbu2008/pollen. – Date of access : 01.06.2015.
11. Identifying Sub-cellular Organelles [Electronic resource]. – 2013. – Mode of access : http://ome.grc.nia.nih.gov/iicbu2008/hela/index.html. – Date of access : 01.06.2015.
12. JSRT Database [Electronic resource]. – 2013. – Mode of access : http://www.jsrt.or.jp/jsrtdb/ eng.php. – Date of access : 01.06.2015.
13. Ковалев, В.А. Влияние мер близости в пространстве признаков на качество поиска медицинских изображений по содержанию / В.А. Ковалев, А.А. Дмитрук // Информатика. – 2011. – № 30. – С. 5–11.
14. Дмитрук, А.А. Обнаружение узловых образований в легком по данным компьютерной томографии / А.А. Дмитрук // Информатика. – 2011. – № 29. – С. 25–33.
15. The Database of Faces [Electronic resource]. – 2013. – Mode of access : http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html. – Date of access : 01.06.2015.
16. Yale Face Database [Electronic resource]. – 2013. – Mode of access : http://vision.ucsd. edu/content/yale-face-database. – Date of access : 01.06.2015.
17. WND-CHARM: Multi-purpose image classification using compound image transforms / N. Orlov [et al.] // Pattern recognition letters. – 2008. – Vol. 29, № 11. – P. 1684–1693.
18. General pattern recognition in images using WND-CHARM [Electronic resource]. – 2013. – Mode of access : http://ome.grc.nia.nih.gov/wnd-charm. – Date of access : 01.06.2015.
19. Ковалев, В.А. Анализ структуры трехмерных медицинских изображений / В.А. Ковалев. – Минск : Белорус. наука, 2008. – 263 c.
20. Dalal, N. Histograms of oriented gradients for human detection / N. Dalal, B. Triggs // Computer Vision and Pattern Recognition. CVPR 2005. IEEE Computer Society Conf. – Montbonnot- Saint-Martin, 2005. – Vol. 1. – P. 886–893.
21. A general Local Binary Pattern (LBP) implementation for Matlab [Electronic resource]. – 2013. – Mode of access : http://www.cse.oulu.fi/CMV/Downloads/LBPMatlab. – Date of access : 01.06.2015.
22. Pietikainen, M. Computer vision using local binary patterns / M. Pietikainen. – Springer, 2011. – Vol. 40. – 207 p.
23. Improved medical image modality classification using a combination of visual and textual features / I. Dimitrovski [et al.] // Computerized Medical Imaging and Graphics. – 2015. – Vol. 39. – P. 14–26.
24. Color and texture descriptors / B.S. Manjunath [et al.] // IEEE Transactions on Circuits and Systems for Video Technology. – 2001. – Vol. 11, № 6. – P. 703–715.
Review
For citations:
Dmitruk А.А. COMPARATIVE STUDY OF DESCRIPTORS FOR MEDICAL IMAGE RETRIEVAL. Informatics. 2015;(3):5-12. (In Russ.)
Views: 727
Email this article 