Imperial College London

DR BERNHARD KAINZ

Faculty of EngineeringDepartment of Computing

Reader in Medical Image Computing
 
 
 
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Contact

 

+44 (0)20 7594 8349b.kainz Website CV

 
 
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Location

 

372Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inbook{Baugh:2022:10.1007/978-3-031-16749-2_10,
author = {Baugh, M and Tan, J and Vlontzos, A and Mueller, JP and Kainz, B},
doi = {10.1007/978-3-031-16749-2_10},
editor = {Sudre and Baumgartner and Dalca and Qin and Tanno and VanLeemput and Wells},
pages = {103--112},
publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},
title = {nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods},
url = {http://dx.doi.org/10.1007/978-3-031-16749-2_10},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - CHAP
AU - Baugh,M
AU - Tan,J
AU - Vlontzos,A
AU - Mueller,JP
AU - Kainz,B
DO - 10.1007/978-3-031-16749-2_10
EP - 112
PB - SPRINGER INTERNATIONAL PUBLISHING AG
PY - 2022///
SN - 978-3-031-16748-5
SP - 103
TI - nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods
UR - http://dx.doi.org/10.1007/978-3-031-16749-2_10
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000877066500010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
ER -