PENet: Continuous-Valued Pulmonary Edema Severity Prediction On Chest X-ray Using Siamese Convolutional Networks
Author:
Affiliation:
1. Philips Research North America,Radiology Informatics group,Dept. of Precision Diagnostics and Image Guided Therapy,Cambridge,MA,USA
2. Northeastern University,Cognitive Systems Lab,Dept. of Electrical & Computer Engineering,Boston,MA,USA,02134
Funder
Philips Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871153.pdf?arnumber=9871153
Reference14 articles.
1. Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs;johnson;ArXiv Preprint,2019
2. Densely Connected Convolutional Networks
3. CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
4. Multimodal Representation Learning via Maximization of Local Mutual Information
5. Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation
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