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Reviewed Medical Image Datasets:
1. NIH Clinical Center:
Chest X-Ray Dataset (ChestX-ray8): Contains over 100,000 frontal-view X-ray images of 30,805 unique patients with 14
disease labels…
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Shiraishi, J., et al.: Development of a digital image database for chest radiographs
with and without a lung nodule: receiver operating characteristic analysis of radiologists’
detection of pulmonar…
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The MIMIC-CXR dataset is a large publicly available dataset
of chest radiographs in the JPEG format with structured labels derived from
free-text radiology reports. The dataset contains 377,110 JPEG…
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These are the published projects that still have possibly broken lists of references (see issue #2137):
Broken version
Older version
bionlp-workshop-2023-task-1a/2.0.0
bionlp-workshop-2023-task-…
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http://dx.doi.org/10.1148/radiol.2017162326
> **Purpose**
To evaluate the efficacy of deep convolutional neural networks (DCNNs) for detecting tuberculosis (TB) on chest radiographs.
**Materials …
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Hello, I am a beginner at python programming, considering to use your bone-suppression model for my radiology research.
About a hundred chest radiographs in DICOM data are retrieved for evaluation. …
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Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation
论文:https://arxiv.org/pdf/1603.08486v1.pdf
代码:
Interleaved text/image deep mining on a very largesc…
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Medical would be good? Single band would also be good to test. Something with a permissive license.
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[explain](https://radiopaedia.org/articles/cardiothoracic-ratio)
The cardiothoracic ratio (CTR) aids in the detection of [enlargement of the cardiac silhouette](https://radiopaedia.org/articles/enl…