Feng Li
Orcid: 0000-0001-8302-6174Affiliations:
- University of Chicago, Department of Radiology, Kurt Rossmann Laboratories for Radiologic Image Research, IL, USA
According to our database1,
Feng Li
authored at least 20 papers
between 2003 and 2023.
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Online presence:
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Bibliography
2023
Convolutional Neural Networks for Segmentation of Malignant Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).
CoRR, 2023
2021
Anatomic Point-Based Lung Region with Zone Identification for Radiologist Annotation and Machine Learning for Chest Radiographs.
J. Digit. Imaging, 2021
Radiomic texture analysis for the assessment of osteoporosis on low-dose thoracic CT scans.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
2020
Network output visualization to uncover limitations of deep learning detection of pneumothorax.
Proceedings of the Medical Imaging 2020: Image Perception, 2020
Deep learning for pneumothorax detection and localization using networks fine-tuned with multiple institutional datasets.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2017
Automated assessment of imaging biomarkers for the PanCan lung cancer risk prediction model with validation on NLST data.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
2010
True Detection Versus "Accidental" Detection of Small Lung Cancer by a Computer-Aided Detection (CAD) Program on Chest Radiographs.
J. Digit. Imaging, 2010
Usefulness of texture features for segmentation of lungs with severe diffuse interstitial lung disease.
Proceedings of the Medical Imaging 2010: Computer-Aided Diagnosis, San Diego, 2010
2009
A novel scheme for detection of diffuse lung disease in MDCT by use of statistical texture features.
Proceedings of the Medical Imaging 2009: Computer-Aided Diagnosis, 2009
2008
Proceedings of the Medical Imaging 2008: Image Processing, 2008
Proceedings of the Medical Imaging 2008: Computer-Aided Diagnosis, San Diego, 2008
Performance levels for computerized detection of nodules in different size and pattern groups on thin-slice CT.
Proceedings of the Medical Imaging 2008: Computer-Aided Diagnosis, San Diego, 2008
2007
Computerized method for detection of vertebral fractures on lateral chest radiographs based on morphometric data.
Proceedings of the Medical Imaging 2007: Computer-Aided Diagnosis, San Diego, 2007
2006
Development of computerized method for detection of vertebral fractures on lateral chest radiographs.
Proceedings of the Medical Imaging 2006: Image Processing, 2006
2005
Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network.
IEEE Trans. Medical Imaging, 2005
Effect of massive training artificial neural networks for rib suppression on reduction of false positives in computerized detection of nodules on chest radiographs.
Proceedings of the Medical Imaging 2005: Image Processing, 2005
Computerized nodule detection in thin-slice CT using selective enhancement filter and automated rule-based classifier.
Proceedings of the Medical Imaging 2005: Image Processing, 2005
2004
Suppression of the contrast of ribs in chest radiographs by means of massive training artificial neural network.
Proceedings of the Medical Imaging 2004: Image Processing, 2004
Usefulness of computerized scheme for differentiating benign from malignant lung nodules on high-resolution CT.
Proceedings of the CARS 2004. Computer Assisted Radiology and Surgery. Proceedings of the 18th International Congress and Exhibition, 2004
2003
Effect of a small number of training cases on the performance of massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT.
Proceedings of the Medical Imaging 2003: Image Processing, 2003