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Content based radiology image retrieval using a fuzzy rule based scalable composite descriptor

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Abstract

The rapid advances made in the field of radiology, the increased frequency in which oncological diseases appear, as well as the demand for regular medical checks, led to the creation of a large database of radiology images in every hospital or medical center. There is now an imperative need to create an effective method for the indexing and retrieval of these images. This paper proposes a new method of content based radiology medical image retrieval. The description of images relies on a Fuzzy Rule Based Compact Composite Descriptor (CCD), which includes global image features capturing both brightness and texture characteristics in a 1D Histogram. Furthermore, the proposed descriptor includes the spatial distribution of the information it describes. The most important feature of the proposed descriptor is that its size adapts according to the storage capabilities of the application that uses it. Experiments carried out on a large group of images show that even at 48 bytes per image, the proposed descriptor demonstrates a high level of accuracy in its results. To evaluate the performance of the proposed feature, the mean average precision was used.

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Notes

  1. http://www.img-rummager.com

  2. http://www.anaktisi.net

  3. ACSL: http://www.ee.duth.gr/acsl

  4. IRMA is courtesy of TM Deserno, Dept. of Medical Informatics, RWTH Aachen.

  5. http://www.ee.duth.gr/acsl/results

References

  1. Caicedo JC, Gonzalez FA, Triana E, Romero E (2007) Design of a medical image database with content-based retrieval capabilities. In: Lecture notes in computer science, vol 4872. Springer, New York

    Google Scholar 

  2. Chatzichristofis SA, Boutalis YS (2007) A hybrid scheme for fast and accurate image retrieval based on color descriptors. In: IASTED international conference on artificial intelligence and soft computing (ASC 2007), Spain

  3. Chatzichristofis SA, Boutalis YS (2008) CEDD: color and edge directivity descriptor—a compact descriptor for image indexing and retrieval. In: 6th international conference in advanced research on computer vision systems, ICVS 2008, pp 312–322

  4. Chatzichristofis SA, Boutalis YS (2008) FCTH: fuzzy color and texture histogram—a low level feature for accurate image retrieval. In: 9th international workshop on image analysis for multimedia interactive services, pp 191–196

  5. Chatzichristofis SA, Boutalis YS (2009) Content based medical image indexing and retrieval using a fuzzy compact composite descriptor. In: The sixth IASTED international conference on signal processing, pattern recognition and applications, SPPRA 2009:1–6

  6. Chatzichristofis SA, Boutalis YS, Lux M (2009) Img(Rummager): an interactive content based image retrieval system. In: 2nd international workshop on similarity search and applications (SISAP)

  7. Chee SW, Dong KP, Soo-Jun P (2002) Efficient use of MPEG-7—edge histogram descriptor. ETRI J. 24:23–30

    Article  Google Scholar 

  8. Chi Z, Yan H, Pham T (1996) Fuzzy algorithms: with applications to image processing and pattern recognition. In: Advance in fuzzy systems, applications and theory, vol 10. World Scientific, Singapore

  9. Chu W, Hsu C, Cardenas A, Taira R (1998) Knowledge-based image retrieval with spatial and temporal constructs. IEEE Trans Knowl Data Eng 10(6):872–888

    Article  Google Scholar 

  10. Comaniciu D, Meer P, Foran D, Medl E (1998) Bimodal system for interactive indexing and retrieval of pathology images. In: Workshop on applications of computer vision. Princeton, NJ, pp 76–81

  11. Datta R, Joshi D, Li J, Wang JZ (2008) Image retrieval: ideas, influences, and trends of the new age. ACM Comput Surv 40(2):1–60

    Article  Google Scholar 

  12. Deselaers T, Weyand T, Keysers D, Macherey W, Ney H (2006) FIRE in ImageCLEF 2005: combining content-based image retrieval with textual information retrieval. In: Lecture notes in computer science, vol 4022. Springer, New York

    Google Scholar 

  13. Deselaers T, Keysers D, Ney H (2007) Features for image retrieval: an experimental comparison. Inf Retr 11(2):77–107

    Article  Google Scholar 

  14. Deselaers T, Muller H, Deserno TM (2008) Automatic medical image annotation in ImageCLEF 2007. Pattern Recogn Lett 29(15):1988–1995

    Article  Google Scholar 

  15. Dhawan A (2003) Medical image analysis. Wiley-IEEE, New York

    Google Scholar 

  16. Glatard T, Montagnat J, Magnin I (2004) Texture based medical image indexing and retrieval: application to cardiac imaging. In: 6th ACM SIGMM international workshop on multimedia information retrieval, MIR ’04. ACM, New York, pp 135–142

    Chapter  Google Scholar 

  17. Guld MO, Keysers D, Deselaers T, Leisten M, Schubert H, Ney H, Lehmann TM (2004) Comparison of global features for categorization of medical images. In: Proceedings SPIE, vol 5371, pp 211–222

  18. Guld MO, Thies C, Fischer B, Lehmann TM (2006) Content-based retrieval of medical images by combining global features. In: Lecture notes in computer science, accessing multilingual information repositories

  19. Gustafson EE, Kessel WC (1979) Fuzzy clustering with a fuzzy covariance matrix. In: 18th IEEE conference on decision and control. IEEE CDC, San Diego, pp 761–766

    Google Scholar 

  20. Jeong S, Kim K, Chun B, Lee J, Bae YJ (1999) An effective method for combining multiple features of image retrieval. In: IEEE Region 10 conference: TENCON99, pp 982–985

  21. Keys R (1981) Cubic convolution interpolation for digital image processing. IEEE Trans Signal Process Acoust Speech Signal Process 29:1153

    Article  MATH  MathSciNet  Google Scholar 

  22. Korn F, Sidiropoulos N, Faloustos C, Siegel E, Protopapas Z (1998) Fast and effective retrieval of medical tumor shapes. IEEE Trans Knowl Data Eng 10(6):889–904

    Article  Google Scholar 

  23. Lehmann TM, Guld MO, Keysers D, Deselaers T, Schubert H, Wein B, Spitzer K (2004) Similarity of medical images computed from global feature vectors for content-based retrieval. In: Negoita MGh et al (eds) KES 2004, LNAI, vol 3214. Springer, Berlin, pp 989–995

    Google Scholar 

  24. Lux M, Chatzichristofis SA (2008) LIRe: lucene image retrieval - an extensible java cbir library. In: ACM MM 2008. Vancouver Canada, pp 1085–1087

  25. Luz A Jr, Abdala DD, Wangenheim AV, Comunello E (2006) Analyzing DICOM and non-DICOM features in content-based medical image retrieval: a multi-layer approach. In: Proceedings of the 19th IEEE symposium on computer-based medical systems. IEEE Computer Society, Washington, DC, pp 93–98

    Chapter  Google Scholar 

  26. Manjunath BS, Ohm J-R, Vasudevan VV, Yamada A (2001) Color and texture descriptors. IEEE Trans Circuits Syst Video Technol 11(6):703–715

    Article  Google Scholar 

  27. Mertzios B, Tsirikolias K (2004) Mitra S, Sicuranza G (eds) Logic filters: theory and applications, nonlinear image processing, Chapter 11. Academic, London (ISBN:0125004516)

  28. Muller H, Muller W, Squire DM, Marchand-Maillet S, Pun T (2001) Performance evaluation in content-based image retrieval: overview and proposals. Pattern Recogn Lett 22(5):593–601 (Special Issue on Image and Video Indexing)

    Article  Google Scholar 

  29. Nikolaou N, Papamarkos N (2002) Color image retrieval using a fractal signature extraction technique. Eng Appl Artif Intell 15:81–96

    Article  Google Scholar 

  30. Pianykh OS (2008) Digital imaging and communications in medicine (DICOM): a practical introduction and survival guide. Springer, New York

    Google Scholar 

  31. Poullot S, Buisson O, Crucianu M (2007) Z-grid-based probabilistic retrieval for scaling up content-based copy detection. In: CIVR ’07: proceedings of the 6th ACM international conference on image and video retrieval, pp 348–355

  32. Puzicha J, Rubner Y, Tomasi C, Buhmann J (1999) Empirical evaluation of dissimilarity measures for color and texture. In: Proceedings of the international conference on computer vision, vol 2, pp 1165–1173

  33. Prusinkiewicz P, Hanan J (1989) Lindenmayer systems, fractals, and plants. Springer, Berlin

    MATH  Google Scholar 

  34. Sagan H (1994) Space filling curves. Springer, New York

    MATH  Google Scholar 

  35. Serratosa F, Sanfeliu A (2006) Signatures versus histograms: definitions, distances and algorithms. Pattern Recogn 39:921–934

    Article  MATH  Google Scholar 

  36. Tagare HD, Jaffe CC, Duncan J (1997) Medical image databases a content-based retrieval approach. J Am Med Inform Assoc 4(3):184–198

    Google Scholar 

  37. Tamura H, Mori S, Yamawaki T (1978) Textural features corresponding to visual perception. IEEE Trans Syst Man Cybern 8(6):460–472

    Article  Google Scholar 

  38. Vonikakis V, Andreadis I, Gasteratos A (2008) Fast centre-surround contrast modification. IET Image Processing 2(1):19–34

    Article  Google Scholar 

  39. Willy PM, Karl-Heinz K (2004) Content-based medical image retrieval (CBMIR): an intelligent retrieval system for handling multiple organs of interest. In: 17th IEEE symposium on computer-based medical systems, p 113

  40. Yaoa J, Zhanga Z(Mark), Antanib S, Longb R, Thomab G (2008) Automatic medical image annotation and retrieval. Neurocomputing 71(10–12):2012–2022

    Google Scholar 

  41. Zagoris K, Chatzichristofis SA, Nikolas P, Boutalis YS (2009) Img(Anaktisi): a web content based image retrieval system. In: 2nd international workshop on similarity search and applications (SISAP)

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Correspondence to Savvas A. Chatzichristofis.

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Chatzichristofis, S.A., Boutalis, Y.S. Content based radiology image retrieval using a fuzzy rule based scalable composite descriptor. Multimed Tools Appl 46, 493–519 (2010). https://doi.org/10.1007/s11042-009-0349-x

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