nach oben

Cluster Computing

Erschienen in:

13.01.2018

A novel method to detect bleeding frame and region in wireless capsule endoscopy video

verfasst von: P. Sivakumar, B. Muthu Kumar

Erschienen in: Cluster Computing | Sonderheft 5/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

To detect the region and bleeding frame in the wireless capsule endoscopy video, an automatic computer-aided technique is highly demanded to reduce the burden of physicians. The wireless capsule endoscopy (WCE), is an imaging technology which is recently established and doesn’t require any wired device. This device detects abnormalities in GI tract, i.e. (colon, esophagus, small intestine, and stomach). A WCE video consists of 57,000 images. It is very hard to examine by clinicians. To determine bleeding photos out of fifty-seven thousand WCE images makes the task very hard and expensive. The main goal is to develop an automatic obscure bleeding detection method by using superpixel segmentation and naive Bayes classifier. Naive Bayes and superpixel segmentation are used for this problem.

Vorheriger Artikel Power alert newscast planning for guaranteeing reliability in mobile wireless sensing element networks

Nächster Artikel Soft computing approach based malicious peers detection using geometric and trust features in P2P networks

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Fu, Y., Zhang, W., Mandal, M., Meng, M.Q.: Computer-aided bleeding detection in WCE video. IEEE J. Biomed. Health Inform. 18(2), 636–42 (2014)CrossRef

Pan, G., Yan, G., Qiu, X., Cui, J.: Bleeding detection in wireless capsule endoscopy based on probabilistic neural network. J. Med. Syst. 35(6), 1477–1484 (2011)CrossRef

Al-Rahayfeh, A.A., Abuzneid, A.A.: Detection of bleeding in wireless capsule endoscopy images using range ratio color. Int. J. Multimed. Appl. 2(2), 1–10 (2010)

Hachama, M., Desolneux, A., Richard, F.J.: Bayesian technique for image classifying registration. IEEE Trans. Image Process. 21(9), 4080–4091 (2012)MathSciNetCrossRef

Amin, M.M., Kermani, S., Talebi, A., Oghli, M.G.: Recognition of acute lymphoblastic leukemia cells in microscopic images using K-means clustering and support vector machine classifier. J. Med. Signals Sens. 5(1), 49–58 (2015)CrossRef

Dilna, C., Gopi, V.P.: A novel method for bleeding detection in Wireless Capsule Endoscopic images. In: IEEE International Conference on Computing and Network Communications (CoCoNet), (2015). https://doi.org/10.1109/CoCoNet.2015.7411289

Maghsoudi, O.H., Alizadeh, M., Mirmomen, M.A.: A computer-aided method to detect bleeding, tumor, and disease regions in Wireless Capsule Endoscopy. In: IEEE Conference on Signal Processing in Medicine and Biology Symposium (SPMB), (2016). https://doi.org/10.1109/SPMB.2016.7846852

Yuan, Y., Li, B., Meng, M.Q.: Bleeding frame and region detection in the wireless capsule endoscopy video. IEEE J. Biomed. Health Inform. 20(2), 624–630 (2016)CrossRef

10.

Suman, S., Malik, A.S., Riegler, M., Ho, S.H., Hilmi, I., Goh, K.L.: Detection and classification of bleeding region in WCE images using color feature. In: Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing, Article No. 17 (2017)

11.

Adam, N., Tachecí, I., Sulík, L., Bureš, J., Krejcar, O.: Automatic blood detection in capsule endoscopy video. J. Biomed. Opt. 21(12), 126007 (2016)CrossRef

12.

Pan, G.B., Yan, G.Z., Song, X.S., Qiu, X.L.: Bleeding detection from wireless capsule endoscopy images using improved Euler distance in CIELab. J. Shanghai Jiaotong Univ. (Science) 15(2), 218–223 (2010)CrossRef

13.

Unnimadhavan, R.: Automated bleeding detection in wireless capsule endoscopy videos. J. Biomed. 5(8), 218–224 (2017)

14.

Maghsoudi, O.H., Talebpour, A., Soltanian-Zadeh, H., Alizadeh, M., Soleimani, H.A.: Informative and uninformative regions detection in WCE frames. J. Adv. Comput. 3(1), 12–34 (2014)

15.

Priya, K., Archana, K.S., Neduncheliyanm, S.: Bleeding detection through wireless capsule endoscopy (WCE). Int. J. Adv. Comput. Technol. (IJACT) 4(1), 5–13 (2015)

16.

Hwang, S., Celebi, M.E.: Polyp detection in wireless capsule endoscopy videos based on image segmentation and geometric feature. In: IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), (2010)

17.

Murthi, A., Suganya, D.: Automatic bleeding frame and region detection for GLCM using artificial neural network. J. Adv. Chem. 12(24), 5613–5620 (2016)

18.

Ashok, V., Murugesan, G.: Detection of retinal area from scanning laser ophthalmoscope images (SLO) using deep neural network. Int. J. Biomed. Eng. Technol. 23(2–4), 303–314 (2017)CrossRef

19.

Coimbra, M., Mackiewicz, M., Fisher, M., Jamieson, C., Soares, J., Silva Cunha, J.P.: Computer vision tools for capsule endoscopy exam analysis. Eurasip NewsLetter 18(1), 1–19 (2007)

Titel: A novel method to detect bleeding frame and region in wireless capsule endoscopy video
verfasst von: P. Sivakumar
B. Muthu Kumar
Publikationsdatum: 13.01.2018
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe Sonderheft 5/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-017-1584-y

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Sonderheft 5/2019

An intelligent intrusion detection system for secure wireless communication using IPSO and negative selection classifier

Towards mobile cloud authentication and gait based security using time warping technique

A light weight FFT based enciphering system for extending the lifetime of mobile ad hoc networks

A novel 3- level energy heterogeneity clustering protocol with hybrid routing for a concentric circular wireless sensor network

A cost-sensitive method for wireless sensor network min beacon node set construction

A novel medical image enhancement algorithm based on improvement correction strategy in wavelet transform domain

Premium Partner