Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images

By W. Kostis, A. Reeves, D. Yankelevitz, C. Henschke. IEEE Transactions on Medical Imaging, 2003

388 citations recorded by the source corpus.

Subfields: Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/36faac3d0f10fe2e80fe56427eeae65af49f64e1

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In Pulmonary and Respiratory Medicine

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Lung cancer classification using neural networks for CT images (2014, neutral): “[11] W.”
Computer analysis of computed tomography scans of the lung: a survey (2006, methodology): “[183] described 3-D algorithms for four different types of nodules, depending on their attachments.”
Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study (2010, methodology): “All ﬁndings were segmented with an in house implementation of an algorithm comparable to (Kostis et al., 2003), where the parameters were adjusted interactively by a human operator until a satisfactory segmentation was obtained.”
A large-scale evaluation of automatic pulmonary nodule detection in chest CT using local image features and k-nearest-neighbour classification (2009, methodology): “We segment the candidate structures using an algorithm described by Kostis et al. (2003) in order to calculate features of the segmented objects.”
Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans (2006, methodology): “[16] was designed for small pulmonary nodules and uses a semi-automatic classification of the target nodule into one of four nodule models, the most important ones representing solitary, vascularized, and juxtapleural”
Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation (2017, methodology): “In morphology methods, morphological operations such as logic opening operation were applied for nodule-attached vessels removal (Kostis et al., 2003), then the connected component selection can separate lung nodules.”
Segmentation of Pulmonary Nodules in Thoracic CT Scans: A Region Growing Approach (2008, methodology): “A morphology based approach was introduced in [15].”