Researchers from the National Institutes of Health in Bethesda, Maryland are using NVIDIA GPUs and deep learning to automatically annotate diseases from chest x-rays.
Accelerated by Tesla GPUs, the team trained their convolutional neural networks on a publicly available radiology dataset of chest x-rays and reports to describe the characteristics of a disease, such as location, severity and the affected organs.
The researchers mention this is the first study (to the best of their knowledge) that mines from a publicly available radiology image and report dataset, not only to classify and detect disease in images, but also to describe their context similar to how a human observer would read.
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Detecting and Labeling Diseases in Chest X-Rays with Deep Learning
Apr 14, 2016
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AI-Generated Summary
- NIH researchers in Bethesda, Maryland used deep learning accelerated by Tesla GPUs to automatically annotate diseases from chest x-rays.
- The team trained convolutional neural networks on a publicly available radiology dataset of chest x-rays and reports to describe disease characteristics such as location, severity and affected organs.
- This study is the first known to mine a publicly available radiology image and report dataset not only to classify and detect disease but also to describe context similar to a human observer.
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