Concepedia

Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge

Adam E. Flanders, Luciano M. Prevedello, George Shih, Safwan S. Halabi, Jayashree Kalpathy–Cramer, Robyn L. Ball, John Mongan, Anouk Stein, Felipe Kitamura, Matthew P. Lungren,

Radiology Artificial Intelligence · 2020 · 208 citations · 7 references

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Concepts

Abstract

This dataset is composed of annotations of the five hemorrhage subtypes (subarachnoid, intraventricular, subdural, epidural, and intraparenchymal hemorrhage) typically encountered at brain CT.

References

7

Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study

Sasank Chilamkurthy, Rohit Ghosh, Swetha Tanamala et al. · The Lancet · 2018 · 994 citations

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Augmenting the National Institutes of Health Chest Radiograph Dataset with Expert Annotations of Possible Pneumonia

George Shih, Carol C. Wu, Safwan S. Halabi et al. · Radiology Artificial Intelligence · 2019 · 330 citations · Full text

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Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning

Weicheng Kuo, Pratik Mukherjee, Jitendra Malik et al. · Proceedings of the National Academy of Sciences · 2019 · 270 citations · Full text

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Challenges Related to Artificial Intelligence Research in Medical Imaging and the Importance of Image Analysis Competitions

Luciano M. Prevedello, Safwan S. Halabi, George Shih et al. · Radiology Artificial Intelligence · 2019 · 167 citations · Full text

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Application of Deep Learning in Neuroradiology: Brain Haemorrhage Classification Using Transfer Learning

Awwal Muhammad Dawud, Kamil Yurtkan, Hüseyin Öztoprak · Computational Intelligence and Neuroscience · 2019 · 143 citations · Full text

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