Paper Info
Title
Quantification of emphysema severity by histogram analysis of CT scans
Abstract
Emphysema is characterized by the destruction and over distension of lung tissue, which manifest on high resolution computer tomography (CT) images as regions of low attenuation. Typically, it is diagnosed by clinical symptoms, physical examination, pulmonary function tests, and X-ray and CT imaging. In this paper we discuss a quantitative imaging approach to analyze emphysema which employs low-level segmentations of CT images that partition the data into perceptually relevant regions. We constructed multi-dimensional histograms of feature values computed over the image segmentation. For each region in the segmentation, we derive a rich set of feature measurements. While we can use any combination of physical and geometric features, we found that limiting the scope to two features – the mean attenuation across a region and the region area – is effective. The subject histogram is compared to a set of canonical histograms representative of various stages of emphysema using the Earth Mover’s Distance metric. Disease severity is assigned based on which canonical histogram is most similar to the subject histogram. Experimental results with 81 cases of emphysema at different stages of disease progression show good agreement against the reading of an expert radiologist.
Year
DOI
Venue
2005
10.1007/11566465_91
MICCAI
Keywords
Field
DocType
distance metric,image segmentation,pulmonary function test,physical examination,ct scan
Histogram,Computer vision,Pattern recognition,Computer science,Segmentation,Metric (mathematics),Disease progression,Image segmentation,Tomography,Quantitative imaging,Artificial intelligence,Limiting
Conference
Volume
Issue
ISSN
8
Pt 1
0302-9743
ISBN
Citations 
PageRank 
3-540-29327-2
3
0.52
References 
Authors
3
6
Name
Order
Citations
PageRank
Paulo R. S. Mendonça161050.38
Dirk R. Padfield214712.99
James C. Ross3788.89
James V. Miller420851.13
Sandeep Dutta530.86
Sardar Mal Gautham630.52