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An automatic texture feature analysis framework of renal tumor: surgical, pathological, and molecular evaluation based on multi-phase abdominal CT

Crossref DOI link: https://doi.org/10.1007/s00330-023-10016-4

Published Online: 2023-08-01

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

Authors

Yang, Huancheng

Liu, Hanlin

Lin, Jiashan

Xiao, Hongwei

Guo, Yiqi

Mei, Hangru

Ding, Qiuxia

Yuan, Yangguang

Lai, Xiaohui

Wu, Kai

Wu, Song https://orcid.org/0000-0003-3504-1630
Funding

Funding for this research was provided by:

The National Natural Science Foundation Fund of China (61931024)

Shenzhen Fundamental Research Program (202208183000146)

The Special Funds for Strategic Emerging Industries Development in Shenzhen (20180309163446298)

Shenzhen Science and Technology Program (RCJC20200714114557005)

Guangdong Basic and Applied Basic Research Foundation (2019A1515110038)
License Information

Text and Data Mining valid from 2023-08-01

Version of Record valid from 2023-08-01
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Article History

Received: 19 April 2023

Revised: 6 June 2023

Accepted: 12 June 2023

First Online: 1 August 2023

Declarations

:

: The scientific guarantor of this publication is Pro. Song Wu, who is the head of the Institute of Urology, Shenzhen University, China. Email address: wusong@szu.edu.cn

: The authors declare no competing interests.

: Kai Wu, who majored in statistics and computer sciences, has significant statistical expertise.

: Informed consent documents are waived by the Institutional Review Board.

: The research ethics committee approval number for this study is KY2022-036-01. All data used in this study were obtained in strict accordance with the approved protocols of the institutional review board.

: • retrospective• texture analysis study• observational• multicenter study

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