Interactive Grow Cut Segmentation on CapsuleEndoscopy Image

S. Padmapriya*, P. Shanmugasundaram**, N. Santhiyakumari***
* PG Scholar, Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Salem, India.
** Assistant Professor, Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Salem, India.
*** Professor and Head, Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Salem, India.
Periodicity:March - May'2014
DOI : https://doi.org/10.26634/jpr.1.1.2823

Abstract

Wireless Capsule Endoscopy (WCE) is a transitional endoscopy, diagnosing disease in gross area of the Gastrointestinal (GI) tract ahead the reach of other endoscopy. Cancer is a leading cause of death. As per WHO report 13 million people were affected by cancer disease every year. Bowel cancer is a third most cancer occurring in the GI system. Recent works addresses various screening methods, and adaptive controls to improve the analysis completion. This paper describes a robust method of segmenting the bowel images and to discriminate the normal and affected location using Lab VIEW. The system shows, that the threshold adjusted (segregation) capsule endoscopic images are emphatic, and sophisticate classification by adequate software used to afford an image as clarion.

Keywords

Wireless Capsule Endoscopy (WCE), Gastrointestinal (GI), Lab VIEW, Virtual Instrument (VI), Watershed.

How to Cite this Article?

Padmapriya, S., Sundaram, P S., and Kumari, N. S. (2014). Interactive Grow cut Segmentation on Capsule Endoscopy Image. i-manager’s Journal on Pattern Recognition, 1(1), 36-41. https://doi.org/10.26634/jpr.1.1.2823

References

[1]. Santi Segue, Michal Drozdzal, Fernando Vilarino, Carolina Malagelada, Frenando Azpiroz, Petia Radeva, and Joridi Vitria, (2012). "Categorization and segmentation of Intestinal content frames for wireless capsule endoscopy”. IEEE Transaction on Information Technology in Biomedicine. Vol. 16, No.6.
[2]. G. Iddan, G. Meron, A. Glukhovsky, and P. Swain, (2000). “Wireless capsule endoscopy”. Nature, Vol. 405, pp.4-7.
[3]. V. Hai, T. Echigo, R. Sagawa, K. Higuchi, T. Arakawa, and Y. Yagi, (2006). “Adaptive control of video display for diagnostic assistance by analysis of capsule endoscopic images”. Proc. 18th Int. Conf. Patteren recognition, Vol.3, pp.980-983.
[4]. Y. Ygi, H. Vu, T. Echigo, R. Sagawa, K. Yagi, M. Higuchi, and T. Arakawa, (2007). “A Diagnosis support system for capsuleendoscopy”. Inflammopharmacology. Vol.5, No.2, pp.78-83.
[5]. H. Vu, R. Sagawa, Y. Yagi, T. Echigo, M. Shiba, K. Higuchi, T. Arakawa, and K. Yagi, (2009). “Evaluating the control of the adaptive display rate for video capsule endoscopy diagnosis”. Proc. 18th Int. Conf. Robot Biomimetic. pp.74-79.
[6]. A. Karargyris and N. Bourbakis, (2011). ”Detection of small bowel polyps and ulcer in wireless capsule endoscopy video's”. IEEE Trans. Biomed Egg., Vol. 58, No. 10, pp. 2777-2786.
[7]. S. Hwang and M. E. Celebi, (2010). “Poly detection in wireless capsule endoscopy videos based on image segmentation and geometric feature”. Proc. IEEE Int. Conf. Acoust. Speech Signal process. pp.678-681.
[8]. F. Vilarino, P. Spyridonos, O. Pujol, J. Radeva, (2006). “Automatic detection of intestinal juices in wireless capsule video endoscopy”. Proc. 18th Int. conf. Pattern recognition., pp. 20-24.
[9]. Najman, L., Schmitt, M. (1996). “Geodesic saliency of watershed contours and hierarchical segmentation”. IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 18, No. 12, pp.1163 – 1173.
[10]. Grau, V., Mewes, A.U.J., (2004). “Improved watershed transform for medical image segmentation using prior information”. Proc. IEEE Trans, Medical imaging. Vol. 23, No. 4, pp.447 – 458.
[11]. Gauch, J. M. “Image segmentation and analysis via multiscale gradient watershed hierarchies” Proc. IEEE Trans. Image Processing., Vol. 8, No. 1, pp.69–79.
[12]. Xiaodong Yang, Li, Houqiang, Xiaobo Zhou. “Nuclei Segmentation Using Marker-Controlled Watershed, Tracking Using Mean-Shift, and Kalman Filter in Time-Lapse Microscopy”. Circuits and systems IEEE Trans. Vol. 53, No. 11, pp.2405 – 2414.
[13]. Pramod Bhat, Mandeep Singh, (2012). ”Classification of Stock using Texture Analysis on CT images”. Proc. Int. Journal of Soft Computing and Engg. Vol. 2, No.3.
[14]. Yun Sub Jung, Young Ho Kim, Dong Ha Lee, Jong Hyo Kim, (2008). “Active Blood Detection in a High Resolution Capsule Endoscopy using Color Spectrum Transformation“. Proc. Int. Conf. on Biomedical egg. And Informatics. Vol. 1, pp.859-862.
[15]. Hossein Ghayoumi Zadeh, Siamak Janianpour, and Javad Haddadnia, (2013). ”Recognition and Classification of the Cancer Cells by Using Image Processing and Lab VIEW” Proc. Int. Journal of Computer Theory and engg, Vol. 5, No.1.
[16]. Freixenet, J., Munoz, X., Raba, D., Marti, J., Cufi, X., (2002). “Yet another survey on image segmentation: Region and boundary information integration”. European Conf. Computer Vision. pp.408– 422.
[17]. Martin, D., Fowlkes, C., Malik, J., (2002). “Learning to detect natural image boundaries using brightness and texture”. Neural Information Processing Systems (NIPS).
[18]. Jianbo Shi and Jitendra Malik, (2000). "Normalized Cuts and Image Segmentation". IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 22, No. 8, pp. 888- 905.
[19]. Leo Grady, (2006). “Random Walks for Image Segmentation". IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 28, No. 1, pp. 1768- 1783.
[20]. A. F. Costa, N. D. Mascarenhas, and M.L.D.A. Netto, (1997). ”Cell Nuclei Segmentation in Noisy Images using Morphological Watersheds”. Proc. of SPIE. Vol. 3164, pp. 314-324.
[21]. Y. Y. Wang, Y. N. Sun, C.C.K. Lin, and M.S. Ju, (2006). ”Nerve Cell Segmentation via Multi-Scale Gradient Watershed Hierarchies”. Engineering in Medicine and Biology Society.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Online 15 15

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.