Local phase tensor features for 3-D ultrasound to statistical shape+pose spine model registration

Ilker Hacihaliloglu, Abtin Rasoulian, Robert N. Rohling, Purang Abolmaesumi

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

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.

Original languageEnglish (US)
Article number6844890
Pages (from-to)2167-2179
Number of pages13
JournalIEEE Transactions on Medical Imaging
Volume33
Issue number11
DOIs
StatePublished - Nov 1 2014
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Gradient energy tensor
  • image registration
  • local phase
  • spinal injection
  • statistical shape model
  • ultrasound

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