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d Original Contribution AUTOMATIC ADAPTIVE PARAMETERIZATION IN LOCAL PHASE
 

Summary: d Original Contribution
AUTOMATIC ADAPTIVE PARAMETERIZATION IN LOCAL PHASE
FEATURE-BASED BONE SEGMENTATION IN ULTRASOUND
ILKER HACIHALILOGLU,* RAFEEF ABUGHARBIEH,* ANTONY J. HODGSON,y
and ROBERT N. ROHLING*y
*Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada; and
y
Department of Mechanical Engineering, University of British Columbia, Vancouver, BC, Canada
(Received 21 October 2010; revised 2 June 2011; in final form 14 June 2011)
Abstract--Intensity-invariant local phase features based on Log-Gabor filters have been recently shown to
produce highly accurate localizations of bone surfaces from three-dimensional (3-D) ultrasound. A key challenge,
however, remains in the proper selection of filter parameters, whose values have so far been chosen empirically and
kept fixed for a given image. Since Log-Gabor filter responses widely change when varying the filter parameters,
actual parameter selection can significantly affect the quality of extracted features. This article presents a novel
method for contextual parameter selection that autonomously adapts to image content. Our technique automati-
cally selects the scale, bandwidth and orientation parameters of Log-Gabor filters for optimizing local phase
symmetry. The proposed approach incorporates principle curvature computed from the Hessian matrix and direc-
tional filter banks in a phase scale-space framework. Evaluations performed on carefully designed in vitro exper-
iments demonstrate 35% improvement in accuracy of bone surface localization compared with empirically-set
parameterization results. Results from a pilot in vivo study on human subjects, scanned in the operating room,

  

Source: Abugharbieh, Rafeef - Department of Electrical and Computer Engineering, University of British Columbia

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences