AUTOMATIC ADAPTIVE PARAMETERIZATION IN LOCAL PHASE FEATURE-BASED BONE SEGMENTATION IN ULTRASOUND

作者：Hacihaliloglu Ilker; Abugharbieh Rafeef^*; Hodgson Antony J; Rohling Robert N

来源：Ultrasound in Medicine and Biology, 2011, 37(10): 1689-1703.

DOI：10.1016/j.ultrasmedbio.2011.06.006

• Ultrasound
• Local phase features
• Principle curvature
• Automatic parameter selection
• Phase symmetry
• Bone
• Segmentation
• Log-Gabor filters
• Orthopaedic

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 automatically 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 directional filter banks in a phase scale-space framework. Evaluations performed on carefully designed in vitro experiments 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, show similar improvements. (E-mail: [e-mail].

• 出版日期2011-10