Artificial Intelligence in Medicine
Volume 50, Issue 1 , Pages 13-21 , September 2010

Fusing visual and clinical information for lung tissue classification in high-resolution computed tomography

  • Adrien Depeursinge

      Affiliations

    • Medical Informatics Service, Geneva University Hospitals and University of Geneva (HUG), Geneva, Switzerland
    • Corresponding Author InformationCorresponding author. Tel.: +41 22 372 8875; fax: +41 22 372 8879.
    • ,
  • Daniel Racoceanu

      Affiliations

    • Image & Pervasive Access Lab (IPAL), Institute for Infocomm Research (I2R), Singapore
    • ,
  • Jimison Iavindrasana

      Affiliations

    • Medical Informatics Service, Geneva University Hospitals and University of Geneva (HUG), Geneva, Switzerland
    • ,
  • Gilles Cohen

      Affiliations

    • Medical Informatics Service, Geneva University Hospitals and University of Geneva (HUG), Geneva, Switzerland
    • ,
  • Alexandra Platon

      Affiliations

    • Emergency Radiology Service, Geneva University Hospitals and University of Geneva (HUG), Geneva, Switzerland
    • ,
  • Pierre-Alexandre Poletti

      Affiliations

    • Emergency Radiology Service, Geneva University Hospitals and University of Geneva (HUG), Geneva, Switzerland
    • ,
  • Henning Müller

      Affiliations

    • Medical Informatics Service, Geneva University Hospitals and University of Geneva (HUG), Geneva, Switzerland
    • Business Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland

Received 19 September 2008 ,Revised 3 September 2009 ,Accepted 29 March 2010.

References 

  1. Flaherty Kevin R, King Talmadge E, Raghu Ganesh, Lynch Joseph P, Colby Thomas V, Travis William D, et al. Idiopathic interstitial pneumonia: what is the effect of a multidisciplinary approach to diagnosis?. Am J Respir Crit Care Med. 2004;170(July):904–910
  2. Stark Paul. High resolution computed tomography of the lungs. UpToDate. Denise S. Basow edition: Waltham, MA; August 2008.
  3. Doi K. Current status and future potential of computer-aided diagnosis in medical imaging. Br J Radiol. 2005;78:3–19
  4. Shyu Chi-Ren, Brodley Carla E, Kak Avinash C, Kosaka Akio, Aisen Alex M, Broderick Lynn S. ASSERT: a physician-in-the-loop content-based retrieval system for HRCT image databases. Comput Vision Image Understand. 1999;750(July/August (1/2)):111–132(Special issue on content-based access for image and video libraries)
  5. Aisen Alex M, Broderick Lynn S, Winer-Muram Helen, Brodley Carla E, Kak Avinash C, Pavlopoulou Christina, et al. Automated storage and retrieval of thin-section CT images to assist diagnosis: system description and preliminary assessment. Radiology. 2003;2280(July (1)):265–270
  6. Ryu Jay H, Olson Eric J, Midthun David E, Swensen Stephen J. Diagnostic approach to the patient with diffuse lung disease. Mayo Clin Proc. 2002;770(November (11)):1221–1227
  7. Mitsunobu F, Mifune T, Ashida K, Hosaki Y, Tsugeno H, Okamoto M, et al. Influence of age and disease severity on high resolution CT lung densitometry in asthma. Thorax. 2001;560(November (11)):851–856
  8. Toussaint Godfried T. The use of context in pattern recognition. Pattern Recognit. 1978;100(January (3)):189–204
  9. Wu Yi, Chang Edward Y, Chen-Chuan Chang Kevin, Smith John R. Optimal multimodal fusion for multimedia data analysis. In: MULTIMEDIA ‘04: proceedings of the 12th annual ACM international conference on Multimedia. ACM, New York, NY, USA. October 2004;p. 572–579
  10. Snoek Cees GM, Worring Marcel, Smeulders Arnold WM. Early versus late fusion in semantic video analysis. In: MULTIMEDIA ‘05: Proceedings of the 13th annual ACM international conference on Multimedia. ACM, New York, NY, USA. November 2005;p. 399–402
  11. Gunes Hatice, Piccardi Massimo. Affect recognition from face and body: early fusion vs. late fusion. In: 2005 IEEE international conference on systems, man and cybernetics, vol. 4. IEEE Computer Society, Big Island, Hawaii. October 2005;p. 3437–3443
  12. Kludas Jana, Bruno Eric, Marchand-Maillet Stephane. Information fusion in multimedia information retrieval. In: Proceedings of 5th international workshop on adaptive multimedia retrieval (AMR), vol. 4918. ACM, Paris, France. July 2007;p. 147–159
  13. Bell Anthony J. The co-information lattice. In: Proceedings of the 4th international symposium on independent component analysis and blind signal separation (ICA2003). Springer, Nara, Japan. April 2003;p. 921–926
  14. Kittler Josef, Hatef Mohamad, Duin Robert PW, Matas Jiri. On combining classifiers. IEEE Trans Pattern Anal Mach Intell. 1998;20(March (3)):226–239
  15. Lam Louisa. Classifier combinations: implementations and theoretical issues. In: MCS’00: proceedings of the first international workshop on multiple classifier systems. Springer-Verlag, London, UK. 2000;p. 77–86
  16. Dietterich Thomas G. Ensemble methods in machine learning. In: MCS’00: proceedings of the first international workshop on multiple classifier systems. Springer-Verlag, London, UK. 2000;p. 1–15
  17. Skurichina Marina, Duin Robert PW. Combining feature subsets in feature selection. In: Multiple classifier systems, vol. 3541, Lecture Notes in Computer Science. Springer; June 2005. p. 165–75.
  18. Westerveld Thijs. Image retrieval: content versus context. In: Recherche d’Informations Assistée par Ordinateur (RIAO’2000) computer-assisted information retrieval, vol. 1. Paris, France: CID; April 2000. p. 276–84.
  19. La Cascia Marco, Sethi Saratendu, Sclaroff Stan. Combining textual and visual cues for content–based image retrieval on the world wide web. In: Content-based access of image and video libraries. Proceedings. IEEE workshop on, Washington, DC, USA: IEEE Computer Society; 1998. p. 24–8.
  20. Lacoste Caroline, Chevallet Jean-Pierre, Lim Joo-Hwee, Thi Hoang Le Diem, Xiong Wei, Racoceanu Daniel, et al. Inter-media concept-based medical image indexing and retrieval with UMLS at IPAL. In: Peters Carol, Clough Paul, Gey Fredric C., Karlgren Jussi, Magnini Bernardo, Oard Douglas W., de Rijke Maarten, Stempfhuber Maximilian, editors, CLEF, Lecture Notes in Computer Science, vol. 4730. Springer; 2007. p. 694–701.
  21. Müller Henning, MichouxF Nicolas , BandonF David , GeissbuhlerF Antoine . A review of content-based image retrieval systems in medicine–clinical benefits and future directions. Int J Med Inform. 2004;73(1):1–23
  22. Hersh William, Kalpathy-Cramer Jayashree, Jensen Jeffery. Medical image retrieval and automated annotation: OHSU at ImageCLEF 2006. In: Peters Carol, Clough Paul, Gey Fredric C, Karlgren Jussi, Magnini Bernardo, Oard Douglas W, de Rijke Maarten, Stempfhuber Maximilian, editors. CLEF, Lecture Notes in Computer Science, vol. 4730. Springer; 2007. p. 660–9.
  23. Chen Qiongyu, Li Guoliang, Leong Tze-Yun, Heng Chew-Kiat. Predicting coronary artery disease with medical profile and gene polymorphisms data. In: Kuhn Klaus A, Warren James R, Leong Tze-Yun, editors. Medinfo 2007: Proceedings of the 12th world congress on health (medical) informatics. Brisbane, Australia: IOS Press; August 2007. p. 1219–1224.
  24. Abe Hiroyuki, Ashizawa Kazuto, Li Feng, Matsuyama Naohiro, Fukushima Aya, Shiraishi Junji, et al. Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease: results of a simulation test with actual clinical cases. Acad Radiol 2004;11(June (1)):29–37.
  25. Zrimec Tatjana, Wong James S. Improving computer aided disease detection using knowledge of disease appearance. Stud Health Technol Inf 2007;129:1324–8.
  26. Uppaluri Renuka, Hoffman Eric A, Sonka Milan, Hartley Patrick G, Hunninghake Gary W, McLennan Geoffrey. Computer recognition of regional lung disease patterns. Am J Respir Crit Care Med 1999;160(August(2)):648–54.
  27. Yoshikazu Uchiyama, Shigehiko Katsuragawa, Hiroyuki Abe, Junji Shiraishi, Feng Li, Qiang Li, et al. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography. Med Phys 2003;30(September(9)):2440–54.
  28. Depeursinge Adrien, Sage Daniel, Hidki Asmâa, Platon Alexandra, Poletti Pierre-Alexandre, et al. Lung tissue classification using Wavelet frames. In: Engineering in Medicine and Biology Society. EMBS 2007. 29th Annual international conference of the IEEE. Lyon, France, August 2007. IEEE Computer Society; 2007. p. 6259-6262.
  29. Depeursinge Adrien, Van De Ville Dimitri, Unser Michael, Müller Henning. Lung tissue analysis using isotropic polyharmonic B-spline wavelets. In: MICCAI 2008 workshop on pulmonary image analysis. New York, USA: Lulu; September 2008. p. 125–134.
  30. Depeursinge Adrien, Iavindrasana Jimison, Hidki Asmâa, Cohen Gilles, Geissbuhler Antoine, Platon Alexandra, et al. A classification framework for lung tissue categorization. In: Andriole Katherine P, Siddiqui Khan M, editors, Medical imaging 2008: PACS and imaging informatics, vol. 6919. San Diego, CA, USA: SPIE; 2008. p. 69190C.
  31. Hidki Asmâa, Müller Henning, Depeursinge Adrien, Poletti Pierre-Alexandre, Geissbuhler Antoine. Putting the image into perspective: the need for domain knowledge when performing image-based diagnostic aid. In: Swiss conference on medical informatics (SSIM 2006), Basel, Switzerland; April 2006.
  32. King Talmagde E.. Approach to the adult with interstitial lung disease. UpToDate. Denise S. Basow edition: Waltham, MA; 2008.
  33. Webb W. Richard, Müller Nestor L., Naidich David P., editors. High-resolution CT of the Lung. Philadelphia, PA, USA: Lippincott Williams & Wilkins; 2001.
  34. Van De Ville Dimitri, Blu Thierry, Unser Michael. Isotropic polyharmonic B-splines: scaling functions and wavelets. IEEE Trans. Image Process 2005;14(November (11)):1798–813.
  35. Cohen Gilles, Hilario Melanie, Sax Hugo, Hugonnet Stephane, Geissbuhler Antoine. Learning from imbalanced data in surveillance of nosocomial infection. Artif Intell Med 2006;37(May (1)):7–18.
  36. Quinlan Ross J. Induction of decision trees. Mach. Learn. 1986;1(March (1)):81–106
  37. Quinlan Ross J. C4. 5: programs for machine learning. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.; 1993;
  38. Perner Petra, Belikova Tatjana P, Yashunskaya Nadeszda I. Knowledge acquisition by symbolic decision tree induction for interpretation of digital images in radiology. In SSPR ‘96: Proceedings of the 6th international workshop on advances in structural and syntactical pattern recognition, vol. 1121. London, UK: Springer-Verlag; 1996. p. 208–19.
  39. Wu Ting-Fan, Lin Chih-Jen, Weng Ruby C. Probability estimates for multi-class classification by pairwise coupling. J. Mach. Learn. Res. 2004;5(August):975–1005
  40. Benmokhtar Rachid, Huet Benoit. Classifier fusion: combination methods for semantic indexing in video content. In: ICANN 2006: international conference on artificial neural networks. Athens, Greece. Springer; 2006;p. 65–74
  41. Pechenizkiy Mykola, Tsymbal Alexey, Puuronen Seppo. PCA-based feature transformation for classification: issues in medical diagnostics. In: CBMS ‘04: proceedings of the 17th IEEE symposium on computer-based medical systems. Washington, DC, USA, June 2004. IEEE Computer Society; 2004;p. 535–540
  42. Hong Se June. Use of contextual information for feature ranking and discretization. IEEE Trans Knowledge Data Eng. 1997;9(5):718–730
  43. Chambellan Arnaud, Chailleux Edmond, Similowski Thomas. Prognostic value of the hematocrit in patients with severe COPD receiving long-term oxygen therapy. Chest. 2005;128(September (3)):1201–1208
  44. Limper Andrew H. Chemotherapy-induced lung disease. Clin Chest Med. 2004;25(March (1)):53–64

PII: S0933-3657(10)00038-2

doi: 10.1016/j.artmed.2010.04.006

Artificial Intelligence in Medicine
Volume 50, Issue 1 , Pages 13-21 , September 2010

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