3D segmentation of prostate ultrasound images using wavelet transform

Hamed Akbari, Xiaofeng Yang, Luma V. Halig, Baowei Fei

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

19 Scopus citations

Abstract

The current definitive diagnosis of prostate cancer is transrectal ultrasound (TRUS) guided biopsy. However, the current procedure is limited by using 2D biopsy tools to target 3D biopsy locations. This paper presents a new method for automatic segmentation of the prostate in three-dimensional transrectal ultrasound images, by extracting texture features and by statistically matching geometrical shape of the prostate. A set of Wavelet-based support vector machines (WSVMs) are located and trained at different regions of the prostate surface. The WSVMs capture texture priors of ultrasound images for classification of the prostate and non-prostate tissues in different zones around the prostate boundary. In the segmentation procedure, these W-SVMs are trained in three sagittal, coronal, and transverse planes. The pre-trained W-SVMs are employed to tentatively label each voxel around the surface of the model as a prostate or non-prostate voxel by the texture matching. The labeled voxels in three planes after post-processing is overlaid on a prostate probability model. The probability prostate model is created using 10 segmented prostate data. Consequently, each voxel has four labels: sagittal, coronal, and transverse planes and one probability label. By defining a weight function for each labeling in each region, each voxel is labeled as a prostate or non-prostate voxel. Experimental results by using real patient data show the good performance of the proposed model in segmenting the prostate from ultrasound images.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2011
Subtitle of host publicationImage Processing
DOIs
StatePublished - Jun 9 2011
Externally publishedYes
EventMedical Imaging 2011: Image Processing - Lake Buena Vista, FL, United States
Duration: Feb 14 2011Feb 16 2011

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7962
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2011: Image Processing
CountryUnited States
CityLake Buena Vista, FL
Period2/14/112/16/11

Keywords

  • Prostate segmentation
  • Support Vector Machines
  • Ultrasound image segmentation
  • Wavelet based segmentation
  • kernel support vector machine
  • transrectal ultrasound image

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

    Akbari, H., Yang, X., Halig, L. V., & Fei, B. (2011). 3D segmentation of prostate ultrasound images using wavelet transform. In Medical Imaging 2011: Image Processing [79622K] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7962). https://doi.org/10.1117/12.878072