Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists' detection performance.

By K. Awai, K. Murao, Akio Ozawa, M. Komi, H. Hayakawa, S. Hori, Y. Nishimura. Radiology, 2004

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Shape-Based Computer-Aided Detection of Lung Nodules in Thoracic CT Images (2009, methodology): “Intensity-based detection methods are usually based on the assumption that lung nodules have relatively higher intensity than those of lung parenchyma and employ techniques such as multiple thresholding [3]; clustering [4]; artificial neural networks [5]; and mathematical morphology [6],”
Computer analysis of computed tomography scans of the lung: a survey (2006, methodology): “a) Candidate detection schemes: For finding nodule candidates, the following techniques have been reported: multiple gray-level thresholding [111]–[113], mathematical morphology [114]–[117], genetic algorithm template matching of Gaussian spheres and discs [118], [119], clustering [120]–[123], conne”