Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps

By Hiroyuki Yoshida, Janne J. Näppi. IEEE Transactions on Medical Imaging, 2001

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Current status and future potential of computer-aided diagnosis in medical imaging. (2005, background): “However, the majority of CAD schemes developed in the past include the detection of breast lesions on mammograms [7, 21–30], the detection of lung nodules in chest radiographs [31–49] and thoracic CT [50–71], and the detection of polyps in CT colonography [72–82].”
Digital Topology and Geometry in Medical Imaging: A Survey (2015, background): “Yoshida and Näppi [39] proposed a set of 3-D”
Shape-Based Computer-Aided Detection of Lung Nodules in Thoracic CT Images (2009, methodology): “This model differs from Gaussian smoothing suggested in [27] or geometric diffusion models (including anisotropic diffusion) introduced by Perona and Malik [28] for image smooth-”
Machine Learning and Radiology (2012, methodology): “…neural networks and binary classification trees (Jerebko et al., 2003b), committees of SVMs (Malley et al., 2003), quadratic discriminant analysis (Yoshida and Nappi, 2001), massive-training artificial neural networks (MTANNs) (Suzuki et al., 2008), and logistic regression (van Ravesteijn et al.,…”