A novel learning based segmentation method for rodent brain structures using MRI

Jinghao Zhou, Sukmoon Chang, Qingshan Liu, George Pappas, Vasilios Boronikolas, Michael Michaelides, Nora D. Volkow, Panayotis K. Thanos, Dimitris Metaxas

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

5 Scopus citations

Abstract

This paper reports a novel method for fully automated segmentation of rodent brain volume by extending the robust active shape models to incorporate an automatic prior shape selection process. This automatic prior shape selection process using support vector machines provides an automatic shape initialization method for further segmentation of rodent brain structures such as Cerebellum, Neocortex, Corpus Callosum, External Capsule, Caudate Putamen, Hippocampus and Ventricles with the robust active shape model framework in magnetic resonance images (MRI). The mean successful rate of this classification method shows 92.2% accuracy compared to the expert-defined ground truth. We also demonstrate the very promising segmentation results of the robust active shape model framework in rodent brain volume.

Original languageEnglish (US)
Title of host publication2008 5th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, Proceedings, ISBI
Pages61-64
Number of pages4
DOIs
StatePublished - 2008
Event2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI - Paris, France
Duration: May 14 2008May 17 2008

Publication series

Name2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Other

Other2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
Country/TerritoryFrance
CityParis
Period5/14/085/17/08

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Keywords

  • Biomedical image processing
  • Image segmentation
  • Learning systems
  • Robust active shape model

Fingerprint

Dive into the research topics of 'A novel learning based segmentation method for rodent brain structures using MRI'. Together they form a unique fingerprint.

Cite this