Abstract
Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select those image regions presenting the highest stable spatio-temporal response. Spatio-temporal stability is achieved by extracting 3D watershed regions on the temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of \(21.5\,\%\) in polyp localization and \(43.78\,\%\) in polyp detection.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kerr, J., Day, P., Broadstock, M., Weir, R., Bidwell, S.: Systematic review of the effectiveness of population screening for colorectal cancer (2007)
Quintero, E., Castells, A., Bujanda, L., Cubiella, J., Salas, D., Lanas, Á., Andreu, M., Carballo, F., Morillas, J.D., Hernández, C., et al.: Colonoscopy versus fecal immunochemical testing in colorectal-cancer screening. N. Engl. J. Med. 366(8), 697–706 (2012)
van Rijn, J.C., Reitsma, J.B., Stoker, J., Bossuyt, P.M., van Deventer, S.J., Dekker, E.: Polyp miss rate determined by tandem colonoscopy: a systematic review. Am. J. Gastroenterol. 101(2), 343–350 (2006)
Barclay, R.L., Vicari, J.J., Doughty, A.S., Johanson, J.F., Greenlaw, R.L.: Colonoscopic withdrawal times and adenoma detection during screening colonoscopy. N. Engl. J. Med. 355(24), 2533–2541 (2006)
Bernal, J., Vilariño, F., Sánchez, F.J.: Towards intelligent systems for colonoscopy. In: Miskovitz, P. (ed.) Colonoscopy, pp. 245–270. INTECH (2011). Doi:10.5772/19748. http://www.intechopen.com/books/colonoscopy/towards-intelligent-systems-for-colonoscopy. ISBN: 978-953-307-568-6
Iwahori, Y., Shinohara, T., Hattori, A., Woodham, R.J., Fukui, S., Bhuyan, M., Kasugai, K.: Automatic polyp detection in endoscope images using a hessian filter. In: Proceedings of MVA, pp. 21–24 (2013)
Bernal, J., Sánchez, F.J., Fernández-Esparrach, G., Gil, D., Rodríguez, C., Vilariño, F.: WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians. Comput. Med. Imaging Graph. 43, 99–111 (2015)
Hwang, S., Oh, J., Tavanapong, W., Wong, J., De Groen, P.C.: Polyp detection in colonoscopy video using elliptical shape feature. In: IEEE International Conference on Image Processing, ICIP 2007, vol. 2, pp. II-465. IEEE (2007)
Tajbakhsh, N., Chi, C., Gurudu, S.R., Liang, J.: Automatic polyp detection from learned boundaries. In: Proceedings of ISBI , pp. 97–100. IEEE (2014)
Wang, Y., Tavanapong, W., Wong, J., Oh, J., de Groen, P.: Part-based multiderivative edge cross-sectional profiles for polyp detection in colonoscopy. IEEE J. Biomed. Health Inform. 18, 1379–1389 (2014)
Ameling, S., Wirth, S., Paulus, D., Lacey, G., Vilarino, F.: Texture-based polyp detection in colonoscopy. In: Meinzer, H.-P., Deserno, T.M., Handels, H., Tolxdorff, T. (eds.) Bildverarbeitung für die Medizin 2009. Informatik aktuell, pp. 346–350. Springer, Heidelberg (2009)
Iakovidis, D.K., Maroulis, D.E., Karkanis, S.A., Brokos, A.: A comparative study of texture features for the discrimination of gastric polyps in endoscopic video. In: Proceedings of IEEE CBMS, pp. 575–580. IEEE (2005)
Coimbra, M.T., Cunha, J.P.S.: MPEG-7 visual descriptors-contributions forautomated feature extraction in capsule. IEEE Trans. Circuits Syst. Video Technol. 16(5), 628–637 (2006)
Tajbakhsh, N., Liang, J., Gurudu, S.R.: Asu-mayo polyp detection database (2015)
Park, S.Y., Sargent, D., Spofford, I., Vosburgh, K.G., et al.: A colon video analysis framework for polyp detection. IEEE Trans. Biomed. Eng. 59(5), 1408–1418 (2012)
Bernal, J., Gil, D., Sánchez, C., Sánchez, F.J.: Discarding non informative regions for efficient colonoscopy image analysis. In: Luo, X., Reich, T., Mirota, D., Soper, T. (eds.) CARE 2014. LNCS, vol. 8899, pp. 1–10. Springer, Heidelberg (2014)
Lin, G., Adiga, U., Olson, K., Guzowski, J.F., Barnes, C.A., Roysam, B.: A hybrid 3d watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry Part A 56(1), 23–36 (2003)
Kuhnigk, J.-M., Hahn, H., Hindennach, M., Dicken, V., Krass, S., Peitgen, H.-O.: Lung lobe segmentation by anatomy-guided 3d watershed transform. In: Medical Imaging, pp. 1482–1490. International Society for Optics and Photonics (2003)
Cohen, J.: Statistical Powe Analysis For the Behavioral Sciences. Lawrence Erlbaum Associates, Hillsdale (1988)
Tukey, J.W.: Comparing individual means in the analysis of variance. Biometrics 5, 99–114 (1949)
Acknowledgments
Work supported by the Spanish project TIN2012-33116, DPI2015-65286-R, and the Secretaria d’Universitats i Recerca de la Generalitat de Catalunya 2014-SGR-1470. Debora Gil is a Serra Hunter fellow.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Gil, D., Javier Sánchez, F., Fernández-Esparrach, G., Bernal, J. (2016). 3D Stable Spatio-Temporal Polyp Localization in Colonoscopy Videos. In: Luo, X., Reichl, T., Reiter, A., Mariottini, GL. (eds) Computer-Assisted and Robotic Endoscopy. CARE 2015. Lecture Notes in Computer Science(), vol 9515. Springer, Cham. https://doi.org/10.1007/978-3-319-29965-5_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-29965-5_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29964-8
Online ISBN: 978-3-319-29965-5
eBook Packages: Computer ScienceComputer Science (R0)