Automated detection of lung nodules in CT scans: preliminary results.

By S. Armato, Maryellen Lissak Giger, H. MacMahon. Medical Physics (Lancaster), 2001

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Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study (2010, background): “A large number of systems for nodule detection have been proposed in the literature (Li et al., 2008; Arimura et al., 2004; Armato et al., 2001, 2002; Bae et al., 2005; Bellotti et al., 2007; Brown et al., 2003; Dehmeshki et al., 2007; Enquobahrie et al., 2007; Farag et al., 2004; Ge et al., 2005;…”
Toward automated segmentation of the pathological lung in CT (2005, background): “detection [3]–[5] and/or characterization [6], [7] of lung cancer”
Computer analysis of computed tomography scans of the lung: a survey (2006, background): “In later papers, Armato and co-workers concentrated on schemes to reduce the number of FPs: rule-based [135], [136], LDA [136], [137], and massive training ANN [136], [138].”
Shape-Based Computer-Aided Detection of Lung Nodules in Thoracic CT Images (2009, methodology): “lung nodule computer-aided detection (CAD) are reported frequently in the literature [3]–[17].”
An Improved Multi-task Learning Approach with Applications in Medical Diagnosis (2008, background): “It is well accepted that CAD systems decrease detection and recognition errors when used as a second reader [2].”