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Dataset (features extracted from chest CT images) accompanying the paper Automatic emphysema detection using weakly labeled HRCT lung images

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modified on 2018-10-31, 12:21

The dataset contains derived features from CT images of patients and controls scanned at two different centers, Frederikshavn and Aalborg.

Each image is represented by 50 feature vectors, where each feature vector describes a volumetric ROIs of size 41 x 41x 41 voxels, extracted at random locations inside the lung mask.

The features extracted are Gaussian scale space features, or histograms of intensity values in the ROI after filtering the image. Here we use eight filters (smoothed image, gradient magnitude, Laplacian of Gaussian, three eigenvalues of the Hessian, Gaussian curvature and eigen magnitude), four scales (0.6, 1.2, 2.4 and 4.8 mm), and histograms of ten bins.


Financial support from the Netherlands Organization for Scientific Research (NWO), grant no. 639.022.010