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Image Analysis for Cystic Fibrosis: Computer-Assisted Airway Wall and Vessel Measurements from Low-Dose, Limited Scan Lung CT Images

Overview of attention for article published in Journal of Digital Imaging, May 2012
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Title
Image Analysis for Cystic Fibrosis: Computer-Assisted Airway Wall and Vessel Measurements from Low-Dose, Limited Scan Lung CT Images
Published in
Journal of Digital Imaging, May 2012
DOI 10.1007/s10278-012-9476-4
Pubmed ID
Authors

Erkan Ü. Mumcuoğlu, Frederick R. Long, Robert G. Castile, Metin N. Gurcan

Abstract

Cystic fibrosis (CF) is a life-limiting genetic disease that affects approximately 30,000 Americans. When compared to those of normal children, airways of infants and young children with CF have thicker walls and are more dilated in high-resolution computed tomographic (CT) imaging. In this study, we develop computer-assisted methods for assessment of airway and vessel dimensions from axial, limited scan CT lung images acquired at low pediatric radiation doses. Two methods (threshold- and model-based) were developed to automatically measure airway and vessel sizes for pairs identified by a user. These methods were evaluated on chest CT images from 16 pediatric patients (eight infants and eight children) with different stages of mild CF related lung disease. Results of threshold-based, corrected with regression analysis, and model-based approaches correlated well with both electronic caliper measurements made by experienced observers and spirometric measurements of lung function. While the model-based approach results correlated slightly better with the human measurements than those of the threshold method, a hybrid method, combining these two methods, resulted in the best results.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 26%
Researcher 4 21%
Professor 2 11%
Student > Master 2 11%
Lecturer 1 5%
Other 1 5%
Unknown 4 21%
Readers by discipline Count As %
Medicine and Dentistry 5 26%
Engineering 2 11%
Mathematics 1 5%
Agricultural and Biological Sciences 1 5%
Psychology 1 5%
Other 3 16%
Unknown 6 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 May 2012.
All research outputs
#20,156,537
of 22,664,644 outputs
Outputs from Journal of Digital Imaging
#928
of 1,044 outputs
Outputs of similar age
#148,260
of 163,461 outputs
Outputs of similar age from Journal of Digital Imaging
#6
of 6 outputs
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So far Altmetric has tracked 1,044 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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