Automatic 3D segmentation of ultrasound images using atlas registration and statistical texture prior

Xiaofeng Yang, David Schuster, Viraj Master, Peter Nieh, Aaron Fenster, Baowei Fei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Scopus citations

Abstract

We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 ± 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2011
Subtitle of host publicationVisualization, Image-Guided Procedures, and Modeling
DOIs
StatePublished - May 16 2011
Externally publishedYes
EventMedical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling - Lake Buena Vista, FL, United States
Duration: Feb 13 2011Feb 15 2011

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7964
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
CountryUnited States
CityLake Buena Vista, FL
Period2/13/112/15/11

Keywords

  • Atlas registration
  • Automatic 3D segmentation
  • Gabor filter
  • Prostate cancer
  • Support vector machine
  • Ultrasound imaging

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Yang, X., Schuster, D., Master, V., Nieh, P., Fenster, A., & Fei, B. (2011). Automatic 3D segmentation of ultrasound images using atlas registration and statistical texture prior. In Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling [796432] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7964). https://doi.org/10.1117/12.877888