Statistical methods for automatic segmentation of elastographic images

Elastography is a new ultrasonic method for measuring tissuespsila elasticity. Besides many and widely acknowledged benefits, the method suffers severe limitations due to the high motion sensitivity and inter-operator dependency to the point where it provides only qualitative information, not having...

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Bibliographic Details
Main Authors: Nedevschi, S., Pantilie, C., Marita, T., Dudea, S.
Format: Conference Proceeding
Language:English
Subjects:
Histograms
Image segmentation
Lesions
Measurement uncertainty
Pixel
Ultrasonic imaging
Video sequences
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Summary:Elastography is a new ultrasonic method for measuring tissuespsila elasticity. Besides many and widely acknowledged benefits, the method suffers severe limitations due to the high motion sensitivity and inter-operator dependency to the point where it provides only qualitative information, not having, until now, any real quantification means. In this paper we present an automatic segmentation method for elastographic images based on statistical techniques. First a probabilistic model is built for every pixel in the image, derived by processing a video sequence instead of a single image. The built image contains the values with highest probability for each pixel. Next a DAEM (Deterministic Annealing Expectation Maximization) method is used for automatic image segmentation. Finally a numerical quantification of tissue elasticity is provided based on the segmentation.
DOI:10.1109/ICCP.2008.4648388