Comparison of Normalization Techniques for Radiomics Features From Magnetic Resonance Imaging in Predicting Histologic Grade of Meningiomas-Reference-Cited by-同舟云学术

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Comparison of Normalization Techniques for Radiomics Features From Magnetic Resonance Imaging in Predicting Histologic Grade of Meningiomas

Published:2024 Issue:2 Volume:28 Page:61
ISSN:2384-1095
Container-title:Investigative Magnetic Resonance Imaging
language:en
Short-container-title:Investig Magn Reson Imaging

Author:

Quang Le Thanh¹^ORCID,Baek Byung Hyun²³^ORCID,Yoon Woong²³^ORCID,Kim Seul Kee²⁴^ORCID,Park Ilwoo¹²³⁵^ORCID

Affiliation:

1. Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Korea.

2. Department of Radiology, Chonnam National University Medical School, Gwangju, Korea.

3. Department of Radiology, Chonnam National University Hospital, Gwangju, Korea.

4. Department of Radiology, Chonnam National University Hwasun Hospital, Hwasun, Korea.

5. Department of Data Science, Chonnam National University, Gwangju, Korea.

Funder

Institute for Information and Communications Technology Promotion

National Research Foundation of Korea

CNUH Biomedical Research Institute

Korean Society of Magnetic Resonance in Medicine

Publisher

XMLink

Link

https://i-mri.org/pdf/10.13104/imri.2024.0010

Reference16 articles.

1. Texture analysis of medical images

2. Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications

3. Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping

4. Correlation between magnetic resonance imaging grading and pathological grading in meningioma

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