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Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN

Crossref DOI link: https://doi.org/10.1007/s11548-018-1733-7

Published Online: 2018-03-19

Published Print: 2018-07

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Xu, Xuanang

Zhou, Fugen

Liu, Bo
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (61601012)

National Key R&D Program of China (2017YFC0113100)
License Information

Text and Data Mining valid from 2018-03-19
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Article History

Received: 5 December 2017

Accepted: 8 March 2018

First Online: 19 March 2018

Compliance with ethical standards

:

: This work is funded by the National Key R&D Program of China (2017YFC0113100) and the National Natural Science Foundation of China (61601012).

: The authors declare that they have no conflict of interest.

: For this type of study formal consent is not required.

: Statement of informed consent is not applicable since the manuscript does not contain any participants’ data.