Semi-Automatic Cell Correspondence Analysis Using Iterative Point Cloud Registration

Chen, S, Gehrer, S, Kaliman, S et al. (7 more authors) (2019) Semi-Automatic Cell Correspondence Analysis Using Iterative Point Cloud Registration. In: Handels, H, Deserno, TM, Maier, A, Maier-Hein, KH, Palm, C and Tolxdorff, T, (eds.) Informatik aktuell. BVM 2019: Bildverarbeitung für die Medizin 2019, 17-19 Mar 2019, Lübeck, Germany. Springer Vieweg , pp. 116-121. ISBN 978-3-658-25325-7

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
  • Chen, S
  • Gehrer, S
  • Kaliman, S
  • Ravikumar, N
  • Becit, A
  • Aliee, M
  • Dudziak, D
  • Merkel, R
  • Smith, AS
  • Maier, A
Editors:
  • Handels, H
  • Deserno, TM
  • Maier, A
  • Maier-Hein, KH
  • Palm, C
  • Tolxdorff, T
Copyright, Publisher and Additional Information:

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019. This is a post-peer-review, pre-copyedit version of an article published in Informatik aktuell. The final authenticated version is available online at: https://doi.org/10.1007/978-3-658-25326-4_26. Uploaded in accordance with the publisher's self-archiving policy.

Dates:
  • Published: 7 February 2019
  • Published (online): 7 February 2019
  • Accepted: 23 November 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 05 Aug 2019 10:14
Last Modified: 07 Feb 2020 01:39
Status: Published
Publisher: Springer Vieweg
Identification Number: 10.1007/978-3-658-25326-4_26
Open Archives Initiative ID (OAI ID):

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