• Türkçe
    • English
  • English 
    • Türkçe
    • English
  • Login
View Item 
  •   DSpace Home
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • WoS İndeksli Yayınlar Koleksiyonu
  • View Item
  •   DSpace Home
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • WoS İndeksli Yayınlar Koleksiyonu
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Fast and accurate semiautomatic haptic segmentation of brain tumor in 3D MRI images

Date

2016

Author

Latifi-Navid, Masoud
Bilen, Murat
Konukseven, Erhan Ilhan
Dogan, Mustafa
Altun, Adnan

Metadata

Show full item record

Abstract

In this study, a novel virtual reality-based interactive method combined with the application of a graphical processing unit (GPU) is proposed for the semiautomatic segmentation of 3D magnetic resonance imaging (MRI) of the brain. The key point of our approach is to use haptic force feedback guidance for the selection of seed points in a bounded volume with similar intensity and gradient. For the automatic determination of a bounded volume of segmentation in real time, parallel computation on the GPU is used. Automatic segmentation is applied in this adjustable bounded spherical volume with a variable diameter, which is controlled according to the edge map acquired from the gradient map. The haptic force feedback is used in order to guide the user to remain in a volume, where the intensity and gradient change are under a defined threshold range. After each seed point selection, the segmentation algorithm works inside the bounded volume of the ball with an adjusted diameter. The proposed segmentation method based on force and visual feedback with the advantage of adjustable bounded volume is not only accurate and effective in narrow spaces near the boundaries of different layers, but also fast in large homogeneous spaces since the radius of the ball increases in such regions. Parallel programming on the GPU is used for computing gradient change in selected directions, which is needed for the self-adjustment of the sphere diameter. Gradient values are used for calculating the haptic force on the CPU in real time. In this study, two haptic devices are used, one for getting haptic force feedback and the other for camera guidance during 3D visualization. A comparison between manual segmentation of MRI by an expert surgeon and the proposed segmentation algorithm is done. The proposed segmentation procedure is completed 4 times faster than the manual segmentation with similar accuracy.

Source

Turkish Journal of Electrical Engineering and Computer Sciences

Volume

24

Issue

3

URI

https://doi.org/10.3906/elk-1308-132
https://hdl.handle.net/20.500.12712/13788

Collections

  • Scopus İndeksli Yayınlar Koleksiyonu [14046]
  • WoS İndeksli Yayınlar Koleksiyonu [12971]



DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 




| Policy | Guide | Contact |

DSpace@Ondokuz Mayıs

by OpenAIRE

Advanced Search

sherpa/romeo

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution AuthorThis CollectionBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution Author

My Account

LoginRegister

Statistics

View Google Analytics Statistics

DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 


|| Policy || Library || Ondokuz University || OAI-PMH ||

Ondokuz Mayıs University, Samsun, Turkey
If you find any errors in content, please contact:

Creative Commons License
Ondokuz University Institutional Repository is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License..

DSpace@Ondokuz Mayıs:


DSpace 6.2

tarafından İdeal DSpace hizmetleri çerçevesinde özelleştirilerek kurulmuştur.