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How to Efficiently Annotate Images for Best-Performing Deep Learning-Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Model

Crossref DOI link: https://doi.org/10.1007/s10278-025-01408-7

Published Online: 2025-01-22

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

Authors

Zhang, Yixin https://orcid.org/0000-0002-3197-7151
Zhao, Shen https://orcid.org/0009-0003-1307-7816
Gu, Hanxue https://orcid.org/0000-0003-2622-753X
Mazurowski, Maciej A. https://orcid.org/0000-0003-4202-8602
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Text and Data Mining valid from 2025-01-22

Version of Record valid from 2025-01-22
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Article History

Received: 20 August 2024

Revised: 26 December 2024

Accepted: 7 January 2025

First Online: 22 January 2025

Declarations

:

: The authors declare no competing interests.

: This is an observational study. All datasets are publicly accessible from published work.

: This study does not involve human subjects.

: This study does not involve human subjects.

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