Semi-automatic Methods for Airway and Adjacent Vessel Measurement in Bronchiectasis Patterns in Lung HRCT Images of Cystic Fibrosis Patients

Airway and vessel characterization of bronchiectasis patterns in lung high-resolution computed tomography (HRCT) images of cystic fibrosis (CF) patients is very important to compute the score of disease severity. We propose a hybrid and evolutionary optimized threshold and model-based method for cha...

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Bibliographic Details
Published in:Journal of digital imaging 2018-10, Vol.31 (5), p.727-737
Main Authors: Naseri, Zeinab, Sherafat, Soghra, Abrishami Moghaddam, Hamid, Modaresi, Mohammadreza, Pak, Neda, Zamani, Fatemeh
Format: Article
Language:English
Subjects:
BIOLOGICAL MARKERS
Biomarkers
Bronchiectasis
Computed tomography
COMPUTERIZED TOMOGRAPHY
Cystic fibrosis
DISEASES
ERRORS
Evolutionary algorithms
FIBROSIS
GENETIC ALGORITHMS
Image enhancement
Image resolution
Imaging
LUNGS
Medicine
Medicine & Public Health
OPTIMIZATION
Particle swarm optimization
Patients
Radiology
RADIOLOGY AND NUCLEAR MEDICINE
REGRESSION ANALYSIS
RESOLUTION
Respiratory tract
Run time (computers)
Sexually transmitted diseases
STD
THICKNESS
Wall thickness
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Summary:Airway and vessel characterization of bronchiectasis patterns in lung high-resolution computed tomography (HRCT) images of cystic fibrosis (CF) patients is very important to compute the score of disease severity. We propose a hybrid and evolutionary optimized threshold and model-based method for characterization of airway and vessel in lung HRCT images of CF patients. First, the initial model of airway and vessel is obtained using the enhanced threshold-based method. Then, the model is fitted to the actual image by optimizing its parameters using particle swarm optimization (PSO) evolutionary algorithm. The experimental results demonstrated the outperformance of the proposed method over its counterpart in R-squared, mean and variance of error, and run time. Moreover, the proposed method outperformed its counterpart for airway inner diameter/vessel diameter (AID/VD) and airway wall thickness/vessel diameter (AWT/VD) biomarkers in R-squared and slope of regression analysis.
ISSN:0897-1889
1618-727X
1618-727X
DOI:10.1007/s10278-018-0076-9