Literature DB >> 29487878

Pulmonary lobe separation in expiration chest CT scans based on subject-specific priors derived from inspiration scans.

Christian Bauer1, Michael Eberlein2, Reinhard R Beichel1,2.   

Abstract

Segmentation of pulmonary lobes in inspiration and expiration chest CT scan pairs is an important prerequisite for lobe-based quantitative disease assessment. Conventional methods process each CT scan independently, resulting typically in lower segmentation performance at expiration compared to inspiration. To address this issue, we present an approach, which utilizes CT scans at both respiratory states. It consists of two main parts: a base method that processes a single CT scan and an extended method that utilizes the segmentation result obtained on the inspiration scan as a subject-specific prior for segmentation of the expiration scan. We evaluated the methods on a diverse set of 40 CT scan pairs. In addition, we compare the performance of our method to a registration-based approach. On inspiration scans, the base method achieved an average distance error of 0.59, 0.64, and 0.91 mm for the left oblique, right oblique, and right horizontal fissures, respectively, when compared with expert-based reference tracings. On expiration scans, the base method's errors were 1.54, 3.24, and 3.34 mm, respectively. In comparison, utilizing proposed subject-specific priors for segmentation of expiration scans allowed decreasing average distance errors to 0.82, 0.79, and 1.04 mm, which represents a significant improvement ([Formula: see text]) compared with all other methods investigated.

Entities:  

Keywords:  chest CT; expiration; inspiration; pulmonary lobe segmentation

Year:  2018        PMID: 29487878      PMCID: PMC5806033          DOI: 10.1117/1.JMI.5.1.014003

Source DB:  PubMed          Journal:  J Med Imaging (Bellingham)        ISSN: 2329-4302


  17 in total

1.  Optimal graph search segmentation using arc-weighted graph for simultaneous surface detection of bladder and prostate.

Authors:  Qi Song; Xiaodong Wu; Yunlong Liu; Mark Smith; John Buatti; Milan Sonka
Journal:  Med Image Comput Comput Assist Interv       Date:  2009

2.  Atlas-driven lung lobe segmentation in volumetric X-ray CT images.

Authors:  Li Zhang; Eric A Hoffman; Joseph M Reinhardt
Journal:  IEEE Trans Med Imaging       Date:  2006-01       Impact factor: 10.048

3.  Optimal surface segmentation in volumetric images--a graph-theoretic approach.

Authors:  Kang Li; Xiaodong Wu; Danny Z Chen; Milan Sonka
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2006-01       Impact factor: 6.226

Review 4.  Review of automatic pulmonary lobe segmentation methods from CT.

Authors:  Tom Doel; David J Gavaghan; Vicente Grau
Journal:  Comput Med Imaging Graph       Date:  2014-10-28       Impact factor: 4.790

5.  Airway tree reconstruction in expiration chest CT scans facilitated by information transfer from corresponding inspiration scans.

Authors:  Christian Bauer; Michael Eberlein; Reinhard R Beichel
Journal:  Med Phys       Date:  2016-03       Impact factor: 4.071

6.  Anatomy-guided lung lobe segmentation in X-ray CT images.

Authors:  Soumik Ukil; Joseph M Reinhardt
Journal:  IEEE Trans Med Imaging       Date:  2009-02       Impact factor: 10.048

7.  An approach for reducing the error rate in automated lung segmentation.

Authors:  Gurman Gill; Reinhard R Beichel
Journal:  Comput Biol Med       Date:  2016-06-29       Impact factor: 4.589

8.  Lung registration with improved fissure alignment by integration of pulmonary lobe segmentation.

Authors:  Alexander Schmidt-Richberg; Jan Ehrhardt; René Werner; Heinz Handels
Journal:  Med Image Comput Comput Assist Interv       Date:  2012

Review 9.  The fissure: interlobar collateral ventilation and implications for endoscopic therapy in emphysema.

Authors:  Theodoor David Koster; Dirk-Jan Slebos
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2016-04-13

10.  Lung Segmentation in 4D CT Volumes Based on Robust Active Shape Model Matching.

Authors:  Gurman Gill; Reinhard R Beichel
Journal:  Int J Biomed Imaging       Date:  2015-10-08
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