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Learning to detect chest radiographs containing lung nodules using visual attention networks
We propose two network architectures for the classification of images likely to contain pulmonary nodules using both weak labels and manually-delineated bounding boxes, when these are available.
Learning what to look in chest X-rays with a recurrent visual attention model
X-rays are commonly performed imaging tests that use small amounts of radiation to produce pictures of the organs, tissues, and bones of the body.
Recurrent Convolutional Networks for Pulmonary Nodule Detection in CT Imaging
In this article we propose a deep artificial neural network architecture, ReCTnet, for the fully-automated detection of pulmonary nodules in CT scans.
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