S. Reuzé

发表

Radiomics in Nuclear Medicine Applied to Radiation Therapy: Methods, Pitfalls, and Challenges.

Irène Buvat, Eric Deutsch, Laurent Dercle, 2018, International journal of radiation oncology, biology, physics.

Prediction of cervical cancer recurrence using textural features extracted from 18F-FDG PET images acquired with different scanners

C. Haie-meder, Cyrus Chargari, Fanny Orlhac, 2017, Oncotarget.

Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology

N. Paragios, E. Zacharaki, S. Reuzé, 2017, Annals of oncology : official journal of the European Society for Medical Oncology.

Influence of Magnetic Field Strength on Magnetic Resonance Imaging Radiomics Features in Brain Imaging, an In Vitro and In Vivo Study

F. Bidault, C. Balleyguier, É. Chouzenoux, 2021, Frontiers in Oncology.

The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features

S. Reuzé, A. Schernberg, R. Sun, 2019, Scientific Reports.

Dosimetry-driven quality measure of brain pseudo Computed Tomography generated from deep learning for MRI-only radiotherapy treatment planning.

N. Paragios, Marvin Lerousseau, M. Vakalopoulou, 2020, International Journal of Radiation Oncology, Biology, Physics.

A score combining baseline neutrophilia and primary tumor SUVpeak measured from FDG PET is associated with outcome in locally advanced cervical cancer

C. Haie-meder, Fanny Orlhac, I. Buvat, 2018, European Journal of Nuclear Medicine and Molecular Imaging.

Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics

Nikos Paragios, Johan Pallud, Théo Estienne, 2020, Scientific Reports.

Increased bone marrow SUVmax on 18F-FDG PET is associated with higher pelvic treatment failure in patients with cervical cancer treated by chemoradiotherapy and brachytherapy

C. Haie-meder, M. Schlumberger, A. Dunant, 2019, Oncoimmunology.

Development of a Machine Learning Classifier Based on Radiomic Features Extracted From Post-Contrast 3D T1-Weighted MR Images to Distinguish Glioblastoma From Solitary Brain Metastasis

E. Dezamis, P. Varlet, C. Oppenheim, 2021, Frontiers in Oncology.

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

Irène Buvat, Jessica Goya-Outi, Frédérique Frouin, 2018, Cancer research.

The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features

S. Reuzé, A. Schernberg, R. Sun, 2019, Scientific Reports.

[Computational medical imaging (radiomics) and potential for immuno-oncology].

Cyrus Chargari, N. Paragios, E. Zacharaki, 2017, Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique.

PH-0532: Standardization of brain MRI across machines and protocols: bridging the gap for MRI-based radiomics

N. Paragios, Marvin Lerousseau, C. Oppenheim, 2020 .

Prediction of cervical cancer recurrence using textural features calculated from 18F-FDG PET images

Cyrus Chargari, Fanny Orlhac, I. Buvat, 2016 .