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2019

Do Lateral Views Help Automated Chest X-ray Predictions?

Bertrand, Hadrien, Hashir, Mohammad, Cohen, Joseph Paul

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Most convolutional neural networks in chest radiology use only the frontal posteroanterior (PA) view to make a prediction.

However the lateral view is known to help the diagnosis of certain diseases and conditions.
The recently released PadChest dataset contains paired PA and lateral views, allowing us to study for which diseases and conditions the performance of a neural network improves when provided a lateral x-ray view as opposed to a frontal posteroanterior (PA) view.
Using a simple DenseNet model, we find that using the lateral view increases the AUC of 8 of the 56 labels in our data and achieves the same performance as the PA view for 21 of the labels.

Do Lateral Views Help Automated Chest X-ray Predictions? · Around

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Computer-aided diagnosis for improved detection of lung nodules by use of posterior-anterior and lateral chest radiographs
Junji Shiraishi, Feng Li, and Kunio Doi · 2006
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Lateral Chest Radiograph: A Systematic Approach
David S Feigin · 2010
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Interpretation of plain chest roentgenogram
Suhail Raoof, David Feigin, Arthur Sung, Sabiha Raoof, Lavanya Irugulpati, and Edward C Rosenow III · 2012
Earlier work this paper cites.
HeMIS: Hetero-modal image segmentation
Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, and Yoshua Bengio · 2016
Earlier work this paper cites.
Densely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q. Weinberger · 2017
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