title: Local phase tensor features for 3-D ultrasound to statistical shape+pose spine model registration.
abstract: Most conventional spine interventions are performed under X-ray fluoroscopy guidance. In recent years, there has been a growing interest to develop nonionizing imaging alternatives to guide these procedures. Ultrasound guidance has emerged as a leading alternative. However, a challenging problem is automatic identification of the spinal anatomy in ultrasound data. In this paper, we propose a local phase-based bone feature enhancement technique that can robustly identify the spine surface in ultrasound images. The local phase information is obtained using a gradient energy tensor filter. This information is used to construct local phase tensors in ultrasound images, which highlight the spine surface. We show that our proposed approach results in a more distinct enhancement of the bone surfaces compared to recently proposed techniques based on monogenic scale-space filters and logarithmic Gabor filters. We also demonstrate that registration accuracy of a statistical shape+pose model of the spine to 3-D ultrasound images can be significantly improved, using the proposed method, compared to those obtained using monogenic scale-space filters and logarithmic Gabor filters.
authors.forename: Ilker
authors.initials: I
authors.lastname: Hacihaliloglu
authors.forename: Abtin
authors.initials: A
authors.lastname: Rasoulian
authors.forename: Robert N
authors.initials: RN
authors.lastname: Rohling
authors.forename: Purang
authors.initials: P
authors.lastname: Abolmaesumi
mesh_terms: D000465:Algorithms; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D013131:Spine / Q000000981:diagnostic imaging*; D014463:Ultrasonography