Detailed vertebral segmentation using part-based decomposition and conditional shape models

Marco Pereañez*, Karim Lekadir, Corné Hoogendoorn, Isaac Castro-Mateos, Alejandro Frangi

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

With the advances in minimal invasive surgical procedures, accurate and detailed extraction of the vertebral boundaries is required. In practice, this is a difficult challenge due to the highly complex geometry of the vertebrae, in particular at the processes. This paper presents a statistical modeling approach for detailed vertebral segmentation based on part decomposition and conditional models. To this end, a Vononoi decomposition approach is employed to ensure that each of the main subparts the vertebrae is identified in the subdivision. The obtained shape constraints are effectively relaxed, allowing for an improved encoding of the fine details and shape variability at all the regions of the vertebrae. Subsequently, in order to maintain the statistical coherence of the ensemble, conditional models are used to model the statistical inter-relationships between the different subparts. For shape reconstruction and segmentation, a robust model fitting procedure is introduced to exclude outlying inter-part relationships in the estimation of the shape parameters. The experimental results based on a database of 30 CT scans show significant improvement in accuracy with respect to the state-of-the-art and the potential of the proposed technique for detailed vertebral modeling.

Original languageEnglish
Title of host publicationRecent Advances in Computational Methods and Clinical Applications for Spine Imaging
EditorsJianhua Yao, Ben Glocker, Tobias Klinder, Shuo Li, Shuo Li
PublisherNewswood Ltd
Pages95-103
Number of pages9
ISBN (Electronic)9783319141473
DOIs
Publication statusPublished - 2015
Event2nd Workshop on Computational Methods and Clinical Applications for Spine Imaging, CSI 2014 held in conjunction with MICCAI 2014 - Boston, United States
Duration: 14 Sept 201414 Sept 2014

Publication series

NameLecture Notes in Engineering and Computer Science
Volume20
ISSN (Print)2078-0958

Conference

Conference2nd Workshop on Computational Methods and Clinical Applications for Spine Imaging, CSI 2014 held in conjunction with MICCAI 2014
Country/TerritoryUnited States
CityBoston
Period14/09/1414/09/14

Fingerprint

Dive into the research topics of 'Detailed vertebral segmentation using part-based decomposition and conditional shape models'. Together they form a unique fingerprint.

Cite this