Phase-Based Level Set Segmentation of Ultrasound Images

Ultrasonic image segmentation is a difficult problem due to speckle noise, low contrast, and local changes of intensity. Intensity-based methods do not perform particularly well on ultrasound images. However, it has been previously shown that these images respond well to local phase-based methods wh...

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Bibliographic Details
Published in:IEEE journal of biomedical and health informatics 2011-01, Vol.15 (1), p.138-147
Main Authors: Belaid, A, Boukerroui, D, Maingourd, Y, Lerallut, Jean-Francois
Format: Article
Language:English
Subjects:
Algorithms
Computer Science
Computer Simulation
Echocardiography
Echocardiography - methods
Feature extraction
Fourier Analysis
Heart Ventricles - anatomy & histology
Heart Ventricles - diagnostic imaging
Humans
Image edge detection
Image Processing, Computer-Assisted - methods
Image segmentation
Kernel
Level set
local phase
Medical Imaging
monogenic signal
Noise
Phantoms, Imaging
segmentation
Studies
Ultrasonic imaging
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Summary:Ultrasonic image segmentation is a difficult problem due to speckle noise, low contrast, and local changes of intensity. Intensity-based methods do not perform particularly well on ultrasound images. However, it has been previously shown that these images respond well to local phase-based methods which are theoretically intensity invariant. Here, we use level set propagation to capture the left ventricle boundaries. The proposed approach uses a new speed term based on local phase and local orientation derived from the monogenic signal, which makes the algorithm robust to attenuation artifact. Furthermore, we use Cauchy kernels, as a better alternative to the commonly used log-Gabor, as pair of quadrature filters for the feature extraction. Results on synthetic and natural data show that the proposed method can robustly handle noise, and captures well the low contrast boundaries.
ISSN:1089-7771
2168-2194
1558-0032
2168-2208
DOI:10.1109/TITB.2010.2090889