Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction-Reference-Cited by-同舟云学术

Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction

Published:2024-03-21 Issue: Volume: Page:
ISSN:2948-2933
Container-title:Journal of Imaging Informatics in Medicine
language:en
Short-container-title:J Digit Imaging. Inform. med.

Author:

Kim Daniel D,Chandra Rajat S,Yang Li,Wu Jing,Feng Xue,Atalay Michael,Bettegowda Chetan,Jones Craig,Sair Haris,Liao Wei-hua,Zhu Chengzhang,Zou Beiji,Kazerooni Anahita Fathi,Nabavizadeh Ali,Jiao Zhicheng,Peng Jian^ORCID,Bai Harrison X

Funder

Alpert Medical School Summer Assistantship award

National Science Foundation of Hunan Province

International Science and Technology Innovation Joint Base of Machine Vision and Medical Image Processing in Hunan Providence

111 project

Hunan Province Key Areas Research and Development Program

Huxiang High-level Talent Gathering Project-Innovation Talent

Natural Science Foundation of China

Natural Science Foundation of Hunan Province

Sheng Hua Yu Ying Project of Central South University

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10278-024-01037-6.pdf

Reference29 articles.

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4. Cristobal-Huerta A, Poot DHJ, Vogel MW, et al. Compressed Sensing 3D-GRASE for faster High-Resolution MRI. Magn Reson Med 2019; 82: 984–999. 20190502.https://doi.org/10.1002/mrm.27789

5. Banerjee I, Bhattacharjee K, Burns JL, et al. “Shortcuts” Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation. J Am Coll Radiol 2023; 20: 842–851. 20230727. https://doi.org/10.1016/j.jacr.2023.06.025

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