Imperial College London
Portrait Picture

Dr Ben Glocker

Faculty of Engineering, Department of Computing

Professor in Machine Learning for Imaging
 
 
 
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Contact

 

+44 (0)20 7594 8334b.glocker Website CV

 
 
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Location

 

377Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Coelho:2020:10.1038/s41467-020-17478-w,
author = {Coelho, De Castro D and Walker, I and Glocker, B},
doi = {10.1038/s41467-020-17478-w},
journal = {Nature Communications},
pages = {1--10},
title = {Causality matters in medical imaging},
url = {http://dx.doi.org/10.1038/s41467-020-17478-w},
volume = {11},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Causal reasoning can shed new light on the major challenges in ma-chine  learning  for  medical  imaging:   scarcity  of  high-quality  annotated data and mismatch between the development dataset and the target environment.  A causal perspective on these issues allows decisions about data collection, annotation, preprocessing, and learning strategies to be made and scrutinized more transparently,  while providing a detailed categorisation of potential biases and mitigation techniques.  Along with worked clinical examples, we highlight the importance of establishing the causal relationship between images and their annotations, and offer step-by-step recommendations for future studies.
AU  - Coelho,De Castro D
AU  - Walker,I
AU  - Glocker,B
DO  - 10.1038/s41467-020-17478-w
EP  - 10
PY  - 2020///
SN  - 2041-1723
SP  - 1
TI  - Causality matters in medical imaging
T2  - Nature Communications
UR  - http://dx.doi.org/10.1038/s41467-020-17478-w
UR  - https://www.nature.com/articles/s41467-020-17478-w
UR  - http://hdl.handle.net/10044/1/88940
VL  - 11
ER  -
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