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Video Processing Architecture: A Solution for Endoscopic Procedures Results

  • Isabel Laranjo
  • Joel Braga
  • Domingos Assunção
  • Carla Rolanda
  • Luís Lopes
  • Jorge Correia-Pinto
  • Victor Alves
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 291)

Abstract

In this paper we propose an architecture for processing endoscopic procedures results. The goal is to create a complete system capable of processing any type of endoscopic multimedia results, in order to overcome the most common issues in the endoscopic domain (e.g. video’s long-duration, gastroenterologist’s possible difficulty to maintain the focus and efficiency during the viewing process, imperfections in images/videos). It was this scenario that led to the conception of the MIVprocessing solution, which will address these and other problems, providing an added value to the elaboration of diagnoses. The MIVprocessing is composed of five tasks: Video Summarization (elimination of the “non-informative” frames); Pre-Processing (correction/improvement of the frames); Pre-Detection; Segmentation; and Feature Extraction and Classification. The idea is to create a framework that brings together the capabilities of different but at the same time complementary concepts (e.g. image and signal processing, machine learning, computer vision). This conjugation applied to the endoscopic domain provides a set of features capable of improving the gastroenterologist’s activities during and after the procedure.

Keywords

Endoscopy White-light Endoscopy e-Health MyEndoscopy MIVprocessing Video Summarization Image and Video Processing 

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References

  1. 1.
    Moeslund, T.B.: Introduction to Video and Image Processing: Building Real Systems and Applications. Springer, London (2012)CrossRefGoogle Scholar
  2. 2.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Pearson Education International (2009)Google Scholar
  3. 3.
    Bui, A.A.T., Taira, R.K., Kangarloo, H.: Introduction - What is Medical Imaging Informatics? In: Bui, A.A.T., Taira, R.K. (eds.) Medical Imaging Informatics, pp. 3–14. Springer US (2010)Google Scholar
  4. 4.
    Schiller, K.F.R., Warren, B.F., Hunt, R.H.: Atlas of Gastrointestinal Endoscopy and Related Pathology. Wiley-Blackwell (2002)Google Scholar
  5. 5.
    Liedlgruber, M., Uhl, A.: Computer-Aided Decision Support Systems for Endoscopy in the Gastrointestinal Tract: a Review. IEEE Rev. Biomed. Eng. 4, 73–88 (2011)CrossRefGoogle Scholar
  6. 6.
    Karargyris, A., Bourbakis, N.: Detection of Small Bowel Polyps and Ulcers in Wireless Capsule Endoscopy Videos. IEEE Trans. Biomed. Eng. 58, 2777–2786 (2011)CrossRefGoogle Scholar
  7. 7.
    Alexandre, L.A., Casteleiro, J.M., Nobreinst, N.: Polyp Detection in Endoscopic Video Using SVMs. In: Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladenič, D., Skowron, A. (eds.) PKDD 2007. LNCS (LNAI), vol. 4702, pp. 358–365. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Barbosa, D.C., Roupar, D.B., Ramos, J.C., Tavares, A.C., Lima, C.S.: Automatic Small Bowel Tumor Diagnosis by using Multi-scale Wavelet-based Analysis in Wireless Capsule Endoscopy Images. Biomed. Eng. Online. 11, 1–17 (2012)CrossRefGoogle Scholar
  9. 9.
    Iakovidis, D.K., Maroulis, D.E., Karkanis, S.: a: An Intelligent System for Automatic Detection of Gastrointestinal Adenomas in Video Endoscopy. Comput. Biol. Med. 36, 1084–1103 (2006)CrossRefGoogle Scholar
  10. 10.
    Chen, Y., Lee, J.: Ulcer Detection in Wireless Capsule Endoscopy Video. In: Proceedings of the 20th ACM International Conference on Multimedia, pp. 1181–1184. ACM (2012)Google Scholar
  11. 11.
    Pan, G., Yan, G., Qiu, X., Cui, J.: Bleeding Detection in Wireless Capsule Endoscopy Based on Probabilistic Neural Network. J. Med. Syst. 35, 1477–1484 (2011)CrossRefGoogle Scholar
  12. 12.
    Li, B., Meng, M.Q.-H.: Computer-Aided Detection of Bleeding Regions for Capsule Endoscopy Images. IEEE Trans. Biomed. Eng. 56, 1032–1039 (2009)CrossRefGoogle Scholar
  13. 13.
    Stehle, T.: Removal of Specular Reflections in Endoscopic Images Removal of Specular Reflections in Endoscopic Images. Acta Polytech. J. Adv. Eng. 46, 32–36 (2006)Google Scholar
  14. 14.
    Bashar, M.K., Kitasaka, T., Suenaga, Y., Mekada, Y., Mori, K.: Automatic Detection of Informative Frames from Wireless Capsule Endoscopy Images. Med. Image Anal. 14, 449–470 (2010)CrossRefGoogle Scholar
  15. 15.
    Lau, P.Y., Correia, P.L.: Analyzing Gastrointestinal Tissue Images using Multiple Features. In: Proceedings of the International Conference on Telecommunications, pp. 435–438 (2007)Google Scholar
  16. 16.
    Laranjo, I., Braga, J., Assunção, D., Silva, A., Rolanda, C., Lopes, L., Correia-Pinto, J., Alves, V.: Web-Based Solution for Acquisition, Processing, Archiving and Diffusion of Endoscopy Studies. In: Omatu, S., Neves, J., Rodriguez, J.M.C., Paz Santana, J.F., Gonzalez, S.R. (eds.) Distrib. Computing & Artificial Intelligence. AISC, vol. 217, pp. 317–324. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  17. 17.
    Braga, J., Laranjo, I., Assunção, D., Rolanda, C., Lopes, L., Correia-Pinto, J., Alves, V.: Endoscopic Imaging Results: Web based Solution with Video Diffusion. Procedia Technol. 9, 1123–1131 (2013)CrossRefGoogle Scholar
  18. 18.
    Oliveira, T., Novais, P., Neves, J.: Guideline Formalization and Knowledge Representation for Clinical Decision Support. Adv. Distrib. Comput. Artif. Intell. J. 1, 1–12 (2012)Google Scholar
  19. 19.
    Aabakken, L., Rembacken, B., LeMoine, O., Kuznetsov, K., Rey, J.-F., Rösch, T., Eisen, G., Cotton, P., Fujino, M.: Minimal Standard Terminology for Gastrointestinal Endoscopy (MST 3.0) (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Isabel Laranjo
    • 1
    • 2
  • Joel Braga
    • 1
    • 2
  • Domingos Assunção
    • 1
  • Carla Rolanda
    • 2
    • 3
    • 4
  • Luís Lopes
    • 5
  • Jorge Correia-Pinto
    • 2
    • 3
    • 6
  • Victor Alves
    • 1
  1. 1.CCTC - Computer Science and Technology CenterUniversity of MinhoBragaPortugal
  2. 2.Life and Health Sciences Research Institute (ICVS), School of Health SciencesUniversity of MinhoBragaPortugal
  3. 3.ICVS/3B’s - PT Government Associate LaboratoryBraga/GuimarãesPortugal
  4. 4.Department of GastroenterologyHospital de BragaBragaPortugal
  5. 5.Department of GastroenterologySanta Luzia HospitalViana do CasteloPortugal
  6. 6.Department of Pediatric SurgeryHospital de BragaBragaPortugal

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