Change in Smoking Habits Affects Lung Density by CT.

Ashraf, Haseem; Bruijne, Marleen de; Lo, Pechin; Shaker, SB; Dirksen, Asger; Tønnesen, A. Dirksen; Dahlbäck, Magnus; Pedersen, JH

doi:10.1164/ajrccm-conference.2009.179.1_meetingabstracts.a5573

Cited by 2 publications

(1 citation statement)

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“…6(b), indicating a difference in density for the two groups. This corresponds well with recent results indicating that lung parenchyma is more dense in healthy smokers than in never smokers possibly due to smoke-induced inflammation [40], [44]. On the other hand, basing the measurements solely on LBP feature histograms results in a slight drift downwards, as seen in Fig.…”

Section: Discussionsupporting

confidence: 92%

Quantitative Analysis of Pulmonary Emphysema Using Local Binary Patterns

Srensen

Shaker

Bruijne

2010

IEEE Trans. Med. Imaging

340

246

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Abstract-We aim at improving quantitative measures of emphysema in computed tomography (CT) images of the lungs. Current standard measures, such as the relative area of emphysema (RA), rely on a single intensity threshold on individual pixels, thus ignoring any interrelations between pixels. Texture analysis allows for a much richer representation that also takes the local structure around pixels into account. This paper presents a texture classification-based system for emphysema quantification in CT images. Measures of emphysema severity are obtained by fusing pixel posterior probabilities output by a classifier. Local binary patterns (LBP) are used as texture features, and joint LBP and intensity histograms are used for characterizing regions of interest (ROIs). Classification is then performed using a nearest neighbor classifier with a histogram dissimilarity measure as distance. A 95.2% classification accuracy was achieved on a set of 168 manually annotated ROIs, comprising the three classes: normal tissue, centrilobular emphysema, and paraseptal emphysema. The measured emphysema severity was in good agreement with a pulmonary function test (PFT) achieving correlation coefficients of up to = 0 79 in 39 subjects. The results were compared to RA and to a Gaussian filter bank, and the texture-based measures correlated significantly better with PFT than did RA.

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Section: Discussionsupporting

confidence: 92%