A clustering algorithm for liver lesion segmentation of diffusion-weighted MR images

Abhinav K. Jha, Jeffrey J. Rodríguez, Renu M. Stephen, Alison T. Stopeck

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

19 Scopus citations

Abstract

In diffusion-weighted magnetic resonance imaging, accurate segmentation of liver lesions in the diffusion-weighted images is required for computation of the apparent diffusion coefficient (ADC) of the lesion, the parameter that serves as an indicator of lesion response to therapy. However, the segmentation problem is challenging due to low SNR, fuzzy boundaries and speckle and motion artifacts. We propose a clustering algorithm that incorporates spatial information and a geometric constraint to solve this issue. We show that our algorithm provides improved accuracy compared to existing segmentation algorithms.

Original languageEnglish (US)
Title of host publication2010 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2010 - Proceedings
Pages93-96
Number of pages4
DOIs
StatePublished - 2010
Event2010 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2010 - Austin, TX, United States
Duration: May 23 2010May 25 2010

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation

Other

Other2010 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2010
CountryUnited States
CityAustin, TX
Period5/23/105/25/10

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Fingerprint Dive into the research topics of 'A clustering algorithm for liver lesion segmentation of diffusion-weighted MR images'. Together they form a unique fingerprint.

Cite this