Decrypting the information captured by MRI-radiomic features in predicting the response to neoadjuvant chemotherapy in breast cancer

Author:

Martin Marie-Judith Saint1,Frouin Frederique1,Malhaire Caroline1,Orlhac Fanny1

Affiliation:

1. Institut Curie, Université Paris Saclay, Inserm U1288, LITO,Orsay,France

Publisher

IEEE

Reference9 articles.

1. MRI texture features from tumor core and margin in the prediction of response to neoadjuvant chemotherapy in patients with locally advanced breast cancer

2. Clever Hans effect found in a widely used brain tumour MRI dataset

3. LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

4. A radiomics pipeline dedicated to Breast MRI: validation on a multi-scanner phantom study;martin;Magn Reson Mater Biol Phys Med,2020

5. How can we combat multicenter variability in MR radiomics? Validation of a correction procedure;orlhac;Eur Radiol,2020

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Precision Enhanced Breast Cancer Prediction Using Deep Learning Models;2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI);2023-12-29

2. Automatic Breast Tumor Segmentation System with Breast Localization Module Based on Dynamic Contrast Enhanced Magnetic Resonance Imaging;Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science;2023-10-20

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