CT screening for lung cancer: five-year prospective experience.

By S. Swensen, J. Jett, T. Hartman, D. Midthun, Sumithra J. Mandrekar, S. Hillman, A. Sykes, G. Aughenbaugh, A. Bungum, K. L. Allen. Radiology, 2005

600 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/108342e008fca4cca3a4b8ae6d8e8e95936d79dc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Pulmonary and Respiratory Medicine

1. B. van Ginneken
2. Mathias Prokop
3. Arnold M. R. Schilham

In Radiology, Nuclear Medicine and Imaging

1. B. van Ginneken
2. Mathias Prokop
3. Arnold M. R. Schilham
4. Keelin Murphy
5. Josien P. W. Pluim

Citations in the corpus

• Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans (2006, methodology): “The presented algorithms were used as a plug-in within the application prototype for oncological therapy monitoring (PulmoTREAT) described in [12].”
• Benefits and Harms of CT Screening for Lung Cancer: A Systematic Review (2012, unknown): “LDCT vs Chest Radiographs NLST,23 2011 53 454 6561 (25) 8807 (33) 1471 (5.”
• A large-scale evaluation of automatic pulmonary nodule detection in chest CT using local image features and k-nearest-neighbour classification (2009, methodology): “Routine screening programmes using low-dose computed tomography (CT) scanning are currently being considered as a possible means to detect the first signs of lung cancer in apparently healthy but high-risk subjects (Gohagan et al., 2005; New York Early Lung Cancer Action Project Investigators, 2007;”