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Nodule detection and generation on chest X-rays: NODE21 Challenge
To address this, we organized a public research challenge, NODE21, aimed at the detection and generation of lung nodules in chest X-rays.
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed.
Automated Estimation of Total Lung Volume using Chest Radiographs and Deep Learning
The optimal models were tested on 291 CXR studies with reference lung volume obtained from PFT.
Deep Learning with robustness to missing data: A novel approach to the detection of COVID-19
The data includes results from 27 laboratory tests and a chest x-ray scored by a deep learning model.
Deep Learning for Chest X-ray Analysis: A Survey
Recent advances in deep learning have led to a promising performance in many medical image analysis tasks.
FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis
The method is tested using a held-out test dataset of 21, 176 chest x-rays (in-distribution) and a set of 14, 821 out-of-distribution x-ray images of incorrect orientation or anatomy.
Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system
A subset of 500 subjects (50% Xpert positive) was reviewed and annotated by 5 expert observers independently to obtain a radiological reference standard.
