Tubular Structure Segmentation Using Spatial Fully Connected Network with Radial Distance Loss for 3D Medical Images

Wang, C, Hayashi, Y, Oda, M et al. (4 more authors) (2019) Tubular Structure Segmentation Using Spatial Fully Connected Network with Radial Distance Loss for 3D Medical Images. In: Lecture Notes in Computer Science. MICCAI 2019: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, 13-17 Oct 2019, Shenzhen, China. Springer Verlag , pp. 348-356. ISBN 9783030322250

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Copyright, Publisher and Additional Information: © Springer Nature Switzerland AG 2019. This is an author produced version of a conference paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Tubular structure segmentation; Spatial FCN; Radial distance loss; Blood vessel; Bronchus
Dates:
  • Accepted: 1 July 2019
  • Published (online): 10 October 2019
  • Published: 10 October 2019
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: 13 May 2020 13:33
Last Modified: 14 May 2020 16:43
Status: Published
Publisher: Springer Verlag
Identification Number: https://doi.org/10.1007/978-3-030-32226-7_39

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