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Interstitial lung diseases (ILD) involve several abnormal imaging patterns observed in computed tomography (CT) images. Accurate classification of these patterns plays a significant role in precise clinical decision making of the extent and nature of the diseases. Therefore it is important for developing automated pulmonary computer-aided detection (CAD) systems. Conventionally, this task relies on experts' manual identification of regions of interest (ROIs) as a prerequisite to diagnosedoi:10.1080/21681163.2015.1124249 pmid:29623248 pmcid:PMC5881940 fatcat:fmqhxhd2unb73cqwne3wqgedai