Phase congruency map driven brain tumour segmentation

Tünde Szilágyi; Michael Brady; Ervin Berényi

doi:10.1117/12.2082630

20 March 2015 Phase congruency map driven brain tumour segmentation

Tünde Szilágyi, Michael Brady, Ervin Berényi

Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 94133O (2015) https://doi.org/10.1117/12.2082630
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Computer Aided Diagnostic (CAD) systems are already of proven value in healthcare, especially for surgical planning, nevertheless much remains to be done. Gliomas are the most common brain tumours (70%) in adults, with a survival time of just 2-3 months if detected at WHO grades III or higher. Such tumours are extremely variable, necessitating multi-modal Magnetic Resonance Images (MRI). The use of Gadolinium-based contrast agents is only relevant at later stages of the disease where it highlights the enhancing rim of the tumour. Currently, there is no single accepted method that can be used as a reference. There are three main challenges with such images: to decide whether there is tumour present and is so localize it; to construct a mask that separates healthy and diseased tissue; and to differentiate between the tumour core and the surrounding oedema. This paper presents two contributions. First, we develop tumour seed selection based on multiscale multi-modal texture feature vectors. Second, we develop a method based on a local phase congruency based feature map to drive level-set segmentation. The segmentations achieved with our method are more accurate than previously presented methods, particularly for challenging low grade tumours.

Citation Download Citation

Tünde Szilágyi, Michael Brady, and Ervin Berényi "Phase congruency map driven brain tumour segmentation", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94133O (20 March 2015); https://doi.org/10.1117/12.2082630

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available