Automatic 3D detection and segmentation of head and neck cancer from MRI data

Zhao, Baixiang and Soraghan, John and Grose, Derek and Doshi, Trushali and Di-Caterina, Gaetano; Tabus, I. and Larabi, C. and Battisti, F. and Egiazarian, K. and Oudre, L. and Beghdadi, A., eds. (2019) Automatic 3D detection and segmentation of head and neck cancer from MRI data. In: Proceedings of the 2018 7th European Workshop on Visual Information Processing, EUVIP 2018. IEEE, FIN. ISBN 9781538668979 (https://doi.org/10.1109/EUVIP.2018.8611759)

[thumbnail of Zhao-etal-EUVIP2018-Automatic-3D-detection-and-segmentation-of-head-and-neck]
Preview
 Text. Filename: Zhao_etal_EUVIP2018_Automatic_3D_detection_and_segmentation_of_head_and_neck.pdf
Accepted Author Manuscript
Download (1MB)| Preview

Abstract

A novel algorithm for automatic head and neck 3D tumour segmentation from magnetic resonance imaging (MRI) is presented. The proposed algorithm pre-processes the MRI data slices to enhance quality and reduce artefacts. An intensity standardisation process is performed between slices, followed by cancer region segmentation of central slice, to get the correct intensity range and rough location of tumour regions. Fourier interpolation is applied to create isotropic 3D MR I volume. A new location-constrained 3D level set method segments the tumour from the interpolated MRI volume. The proposed algorithm is tested on real MRI data. The results show that the novel 3D tumour volume extraction algorithm has an improved dice score and F-measure when compared to the previous 2D and 3D segmentation method.

  • Item type:Book Section
    ID code:65608
    Dates:
    Date
    Event
    17 January 2019
    Published
    20 September 2018
    Accepted
    Notes:© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:02 Oct 2018 11:09
    Last modified:24 Apr 2024 00:07
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/65608
CORE (COnnecting REpositories)