Computed tomographic virtual colonoscopy computer-aided polyp detection in a screening population.

By Ronald M. Summers, Jianhua Yao, P. Pickhardt, M. Franaszek, I. Bitter, D. Brickman, V. Krishna, J. R. Choi, Walter Reed. Gastroenterology, 2005

314 citations recorded by the source corpus.

Subfields: Gastroenterology, Oncology, Radiation

View Paper: https://www.semanticscholar.org/paper/ebae290cf43ee7eba522f0cbeba6c4d3d8c8a344

How researchers see this paper

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

In Oncology

1. Ronald M. Summers
2. Shijun Wang

In Radiation

1. Ronald M. Summers
2. Kenji Suzuki

Citations in the corpus

• eDoctor: machine learning and the future of medicine (2018, methodology): “Summers et al. [51] reported on ML CAD of polyps on CT colonography images, where the authors took 1186 patients with CT colonography images verified by optical colonoscopy, divided the data into training and test data sets and trained a polyp CAD program on the data, showing no significant…”
• Machine Learning and Radiology (2012, background): “Summers et al. (2005) employed curvature-related features to find polyp candidates.”
• Improving Computer-aided Detection using Convolutional Neural Networks and Random View Aggregation (2015, methodology): “There were 79 training and 173 testing polyps ; and 22 training and 37 testing polyps ( , considered as large polyps) in our CTC dataset [27].”