A fully automatic multi-atlas based segmentation method for prostate MR images

Zhiqiang Tian, Lizhi Liu, Baowei Fei

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

10 Scopus citations

Abstract

Most of multi-atlas segmentation methods focus on the registration between the full-size volumes of the data set. Although the transformations obtained from these registrations may be accurate for the global field of view of the images, they may not be accurate for the local prostate region. This is because different magnetic resonance (MR) images have different fields of view and may have large anatomical variability around the prostate. To overcome this limitation, we proposed a two-stage prostate segmentation method based on a fully automatic multi-atlas framework, which includes the detection stage i.e. locating the prostate, and the segmentation stage i.e. extracting the prostate. The purpose of the first stage is to find a cuboid that contains the whole prostate as small cubage as possible. In this paper, the cuboid including the prostate is detected by registering atlas edge volumes to the target volume while an edge detection algorithm is applied to every slice in the volumes. At the second stage, the proposed method focuses on the registration in the region of the prostate vicinity, which can improve the accuracy of the prostate segmentation. We evaluated the proposed method on 12 patient MR volumes by performing a leave-one-out study. Dice similarity coefficient (DSC) and Hausdorff distance (HD) are used to quantify the difference between our method and the manual ground truth. The proposed method yielded a DSC of 83.4%±4.3%, and a HD of 9.3 mm±2.6 mm. The fully automated segmentation method can provide a useful tool in many prostate imaging applications.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2015
Subtitle of host publicationImage Processing
EditorsMartin A. Styner, Sebastien Ourselin
PublisherSPIE
ISBN (Electronic)9781628415032
DOIs
StatePublished - Jan 1 2015
Externally publishedYes
EventMedical Imaging 2015: Image Processing - Orlando, United States
Duration: Feb 24 2015Feb 26 2015

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9413
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2015: Image Processing
CountryUnited States
CityOrlando
Period2/24/152/26/15

Keywords

  • Magnetic resonance imaging (MRI)
  • adaptive threshold
  • edge volume
  • multi-atlas
  • prostate segmentation
  • registration

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'A fully automatic multi-atlas based segmentation method for prostate MR images'. Together they form a unique fingerprint.

  • Cite this

    Tian, Z., Liu, L., & Fei, B. (2015). A fully automatic multi-atlas based segmentation method for prostate MR images. In M. A. Styner, & S. Ourselin (Eds.), Medical Imaging 2015: Image Processing [941340] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9413). SPIE. https://doi.org/10.1117/12.2082229