Multi-resolution convolutional networks for chest X-ray radiograph based lung nodule detection
- 28 October 2019
- journal article
- research article
- Published by Elsevier BV in Artificial Intelligence in Medicine
- Vol. 103, 101744
- https://doi.org/10.1016/j.artmed.2019.101744
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61702337, 61672357, U1713214)
- Science and Technology Funding of Guangdong Province (2018A050501014)
This publication has 41 references indexed in Scilit:
- A Comparison of Computer-Aided Detection (CAD) Effectiveness in Pulmonary Nodule Identification Using Different Methods of Bone Suppression in Chest RadiographsJournal of Digital Imaging, 2013
- Multi-column deep neural network for traffic sign classificationNeural Networks, 2012
- Annual or biennial CT screening versus observation in heavy smokersEuropean Journal of Cancer Prevention, 2012
- Improved Detection of Subtle Lung Nodules by Use of Chest Radiographs With Bone Suppression Imaging: Receiver Operating Characteristic Analysis With and Without LocalizationAmerican Journal of Roentgenology, 2011
- Performance of Radiologists in Detection of Small Pulmonary Nodules on Chest Radiographs: Effect of Rib Suppression With a Massive-Training Artificial Neural NetworkAmerican Journal of Roentgenology, 2009
- A Randomized Study of Lung Cancer Screening with Spiral Computed TomographyAmerican Journal of Respiratory and Critical Care Medicine, 2009
- Performance analysis of a new computer aided detection system for identifying lung nodules on chest radiographsMedical Image Analysis, 2008
- A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public databaseMedical Image Analysis, 2006
- A fast, non-iterative and exact histogram matching algorithmPattern Recognition Letters, 2002
- Development of a Digital Image Database for Chest Radiographs With and Without a Lung NoduleAmerican Journal of Roentgenology, 2000