Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics

Diagnostic Pathology

Volumn 7, Issue 1, 2012, Pages

  Sharma, Harshita ^a,b   Alekseychuk, Alexander ^b   Leskovsky, Peter ^b   Hellwich, Olaf ^b   Anand, R S ^a   Zerbe, Norman ^c   Hufnagl, Peter ^c  

^a INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

^b TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

^c CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

Author keywords

A; Attributed Relational Graphs (ARG); Breast tissue biopsy; Connected components; Graph theoretic; Region of Interest (ROI); search

Indexed keywords

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; AUTOMATION; BIOPSY; BREAST; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; EVALUATION; FEMALE; HUMAN; INFORMATION RETRIEVAL; METHODOLOGY; PATHOLOGY; PREDICTIVE VALUE; STAINING; THEORETICAL MODEL;

ALGORITHMS; AUTOMATION; BIOPSY; BREAST; COMPUTER GRAPHICS; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; PREDICTIVE VALUE OF TESTS; STAINING AND LABELING;

MLCS; MLOWN;

EID: 84866891288     PISSN: None     EISSN: 17461596     Source Type: Journal    
DOI: 10.1186/1746-1596-7-134     Document Type: Article

References (29)

1. Tagare HD, Jaffe CC, Duncan J. Medical image databases:A content-based retrieval approach. J Am Med Inform Assoc 1997, 4(3):184-198. 10.1136/jamia.1997.0040184, 61234, 9147338.
2. Romo D, Romero E, Gonzalez F. Learning regions of interest from low level maps in virtual microscopy. Diagnostic Pathol 2011, 6(Suppl 1):S22.
3. Kayser K, Görtler J, Borkenfeld S, Kayser G. How to measure diagnosis-associated information in virtual slides. Diagnostic Pathol 2011, 6(Suppl 1):S9.
4. Kayser K, Radziszowski D, Bzdyl P, Sommer R, Kayser G. Towards an automated virtual slide screening: theoretical considerations and practical experiences of automated tissue-based virtual diagnosis to be implemented in the Internet. Diagnostic Pathol 2006, 1:10.
5. Kayser G, Riede U, Werner M, Hufnagl P, Kayser K. Towards an automated morphological classification of histological images of common lung carcinomas. Elec J Pathol Histol 2002, 8:022-03.
6. Bilgin C, Demir C, Nagi C, Yener B. Cell-graph mining for breast tissue modeling and classification. Eng Med and Biol Soc, 2007.29th Annual Int Conference of the IEEE 2007, 2007:5311-5314.
7. Altunbay D, Cigir C, Sokmensuer C, Demir C. Color Graphs for Automated Cancer Diagnosis and Grading. IEEE Trans On Biomed Eng 2010, 57(3):665-674.
8. Sudbo J, Marcelpoil R, Reith A. New algorithms based on the Voronoi diagram applied in a pilot study on normal mucosa and carcinomas. Analytical Cellular Pathology 2000, 21(2):71-86.
9. Datta R, Joshi D, Li J, Wang JZ. Image retrieval: Ideas, influences, and trends of the new age. ACM Comput Surveys 2008, 40:1-60.
10. Rui Y, Huang TS, Chang SF. Image retrieval: Current techniques, promising directions, and open issues. J Visual Commun and Image Representation 1999, 10:39-62.
11. Smeulders AWM, Member S, Worring M, Santini S, Gupta A, Jain R. Content-based image retrieval at the end of the early years. IEEE Trans Pattern Anal and Machine Intelligence 2000, 22:1349-1380.
12. Müller H, Michoux N, Bandon D, Geissbuhler A. A review of content-based image retrieval systems in medical applications - clinical benefits and future directions. Int J Med Informatics 2004, 73:1-23.
13. Ballerini L, Li X, Fisher BR, Rees J. A Query-by-Example Content-Based Image Retrieval System of Non-Melanoma Skin Lesions. Proc MICCAI-09 Workshop MCBR-CDS 2009: Medical Content-based Retrieval for Clinical Decision Support, London, Lecture Notes in Computer science, Springer 2009, 5853:31-38.
14. Jaulent MC, Le B, Cao Y, Zapletal E, Degoulet P. A property concept frame representation for flexible image content retrieval in histopathology databases. Proceedings of the Annual Symposium of the American Society for Medical Informatics (AMIA), Los Angeles, CA , USA 2000, 20(Suppl):379-383.
15. University CM The Diamond Project. [http://diamond.cs.cmu.edu/], University CM.
16. Yang L, Jin R, Sukthankar R, Zheng B, Mummert L, Satyanarayanan M, Chen M, Jukic D. Learning Distance Metrics for Interactive Search-Assisted Diagnosis of Mammograms. proceedings of SPIE Medical Imaging 6514,6514H-6514,6514H. 2007, San Diego, CA.
17. Goode A, Chen M, Tarachandani A, Mummert LB, Sukthankar R, Helfrich C, Stefanni A, Fix L, Saltzman J, Satyanarayanan M. Interactive Search of Adipocytes in Large Collections of Digital Cellular Images. proceedings of the International Conference of Multimedia and Expo(ICME) 2007, 695-698. IEEE, Beijing, China.
18. Satyanarayanan M, Sukthankar R, Goode A, Huston L, Mummert L, Wolbach A, Harkes J, Gass R, . Schlosser S The Open Diamond Platform for Discard-based Search. Tech rep School of Computer Science, Carnegie Mellon University 2008, CMU-CS-08-132. [http://diamond.cs.cmu.edu/papers], Schlosser S.
19. Long LR, Antani S, Deserno TM, Thoma GR. Content-Based Image Retrieval in Medicine: Retrospective Assessment, State of the Art, and Future Directions. IJHISI 2009, 4(1):1-16.
20. Zhou XS, Zillner SS, Moller M, Sintek M, Zhan Y, Krishnan A, Gupta A. Semantics and CBIR, A Medical Imaging Perspective. Proc of the ACM International Conference on Image and Video Retrieval Niagara Falls 2008, 571-580. Canada.
21. Dumay CM, van der Geest RJ, Gerbrands JJ, Jansen E, Reiber JHC. Consistent inexact graph matching applied to labelling coronary-segments in arteriograms. Proc. 11th Int. Conference on Pattern Recognition 1992, 439-442. Vol. 3; The Hague, Netherlands.
22. Treméau A, Colantoni P. Regions adjacency graph applied to color image segmentation. IEEE Trans Image Process 2000, 9(4):735. 10.1109/83.841950, 18255446.
23. Conte D, Foggia P, Sansone C, Vento M. How and why pattern recognition and computer vision applications use graphs. Appl Graph Theory in Compu Vision and Pattern Recognit, Studies Comput Intelligence 2007, 52:85-135. Springer Berlin and Heidelberg, Germany.
24. Conte D, Foggia P, Sansone C, . Vento M Thirty Years of Graph Matching in Pattern Recognition. Intl J Pattern Recognit and Artif Intelligence 2004, 18(3):265-298. Vento M.
25. Dijkstra EW. A note on two problems in connexion with graphs. Numerische Mathematik 1, Springer, 1959, 1:269-271.
26. Russell SJ, Norvig P. Artificial Intelligence: A Modern Approach 2003, N J,Prentice Hall, Upper Saddle River.
27. Hart P, Nilsson N, Raphael B. A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Trans Syst Sci and Cybernetics 1968, 4(2):100-107.
28. Patel A Heuristics: A* Search Algorithm. [http://theory.stanford.edu/amitp/GameProgramming/Heuristics.html], Patel A.
29. Boykov Y, Jolly MP. Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images. Int Conference on Comput Vision 2001, 1:105-112.