title   
  

Statistical Region Based Segmentation of Ultrasound Images

Ünal, Gözde and Slabaugh, Greg and Wels, Michael and Fang, Tong and Rao, Bimba (2008) Statistical Region Based Segmentation of Ultrasound Images. (Accepted/In Press)

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Abstract

Segmentation of ultrasound images is a challenging problem due to speckle, which corrupts the image and can result in weak or missing image boundaries, poor signal to noise ratio, and diminished contrast resolution. Speckle is a random interference pattern that is characterized by an asymmetric distribution as well as significant spatial correla- tion. These attributes of speckle are challenging to model in a segmentation approach, so many previous ultrasound segmentation methods simplify the problem by assuming that the speckle is white and/or Gaussian distributed. Unlike these methods, in this paper we present an ultrasound-specific segmentation approach that addresses both the spatial correlation of the data as well as its intensity distribution. We first decorrelate the image and then apply a region-based active contour whose motion is derived from an appropri- ate parametric distribution for maximum likelihood image segmentation. We consider zero-mean complex Gaussian, Rayleigh, and Fisher-Tippett flows, which are designed to model fully formed speckle in the in-phase/quadrature (IQ), envelope detected, and display (log compressed) images, respectively. We present experimental results demon- strating the effectiveness of our method, and compare the results to other parametric and non-parametric active contours.

Item Type:Article
Uncontrolled Keywords:ultrasound imaging, segmentation, statistical segmentation
Subjects:Q Science > QA Mathematics > QA075 Electronic computers. Computer science
ID Code:10693
Deposited By:Gözde Ünal
Deposited On:13 Nov 2008 15:40
Last Modified:29 Oct 2012 16:04

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