Differentiation of benign versus malignant indistinguishable vertebral compression fractures by different machine learning with MRI-based radiomic features-Reference-Cited by-同舟云学术

Differentiation of benign versus malignant indistinguishable vertebral compression fractures by different machine learning with MRI-based radiomic features

Published:2023-04-26 Issue:7 Volume:33 Page:5069-5076
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Zhang Hao,Yuan Genji,Wang Chao,Zhao Hongshun,Zhu Kai,Guo Jianwei,Chen Mingrui,Liu Houchen,Yang Guangjie,Wang Yan,Ma Xuexiao

Funder

National Natural Science Foundation of China

National Key Research and Development Project

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-023-09678-x.pdf

Reference21 articles.

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2. Arevalo-Perez J, Peck KK, Lyo JK et al (2015) Differentiating benign from malignant vertebral fractures using T1 -weighted dynamic contrast-enhanced MRI. J Magn Reson Imaging 42:1039–1047

3. Chee CG, Yoon MA, Kim KW et al (2021) Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT. Eur Radiol 31:6825–6834

4. Li K, Huang L, Lang Z et al (2019) Reliability and validity of different MRI sequences in improving the accuracy of differential diagnosis of benign and malignant vertebral fractures: a meta-analysis. AJR Am J Roentgenol 213:427–436

5. Shanbhogue K, Tong A, Smereka P et al (2021) Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence. Eur Radiol 31:8447–8457

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