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The Segmentation of Multiple Types of Uterine Lesions in Magnetic Resonance Images Using a Sequential Deep Learning Method with Image-Level Annotations

Crossref DOI link: https://doi.org/10.1007/s10278-023-00931-9

Published Online: 2024-01-16

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

Authors

Cui, Yu-meng

Wang, Hua-li

Cao, Rui

Bai, Hong

Sun, Dan

Feng, Jiu-xiang

Lu, Xue-feng
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (82003843)

Natural Science Foundation of Liaoning Province (2020-BS-221)

Dalian Medical Science Research Program (2211023)
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Text and Data Mining valid from 2024-01-16

Version of Record valid from 2024-01-16
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Article History

Received: 28 June 2023

Revised: 25 October 2023

Accepted: 27 October 2023

First Online: 16 January 2024

Declarations

:

: This study was approved by the Institutional Review Board of Dalian Women and Children’s Medical Group before patient information was accessed.

: This study was performed under a waiver for informed consent due to the retrospective nature of the analysis, the anonymity of the data.

: The authors declare no competing interests.

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