Performance of topological texture features to classify fibrotic interstitial lung disease patterns

Purpose: Topological texture features were compared in their ability to classify “honeycombing,” a morphological pattern that is considered indicative for the presence of fibrotic interstitial lung disease in high-resolution computed tomography (HRCT) images. Methods: For 14 patients with known occu...

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Veröffentlicht in:	Medical physics (Lancaster) 2011-04, Vol.38 (4), p.2035-2044
Hauptverfasser:	Huber, Markus B., Nagarajan, Mahesh B., Leinsinger, Gerda, Eibel, Roger, Ray, Lawrence A., Wismüller, Axel
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes methods Computed tomography Computer aided diagnosis computerised tomography feature extraction Humans Image analysis image classification Image Processing, Computer-Assisted - methods image reconstruction image texture Lung - cytology Lung - diagnostic imaging Lung - pathology Lung Diseases, Interstitial - complications Lung Diseases, Interstitial - diagnostic imaging Lung Diseases, Interstitial - pathology lung high-resolution CT Lungs medical image processing Medical image quality Medical image reconstruction Medical imaging Probability theory, stochastic processes, and statistics Pulmonary Fibrosis - complications Pulmonary Fibrosis - diagnostic imaging Pulmonary Fibrosis - pathology quantitative image analysis radial basis function networks Radiologists Reconstruction Statistical analysis supervised learning support vector machines texture analysis Tissues Tomography, X-Ray Computed
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