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Estimation of intra-operator variability in perfusion parameter measurements using DCE-US
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Association of metastatic pattern and molecular status in stage IV non-small cell lung cancer adenocarcinoma
Alison Dormieux
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Clarification of Definitions of Hyperprogressive Disease During Immunotherapy for Non–Small Cell Lung Cancer
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Guidelines and Good Clinical Practice Recommendations for Contrast Enhanced Ultrasound (CEUS) in the Liver – Update 2012
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Prolonged SARS-CoV-2 RNA virus shedding and lymphopenia are hallmarks of COVID-19 in cancer patients with poor prognosis
Anne-Gaëlle Goubet
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Methodology for quantifying interactions between perfusion evaluated by DCE-US and hypoxia throughout tumor growth.
Nicolas Elie
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Molecular Imaging to Predict Response to Targeted Therapies in Renal Cell Carcinoma
Ingrid Leguerney
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Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment
Paul Blanc-Durand
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Jean-Baptiste. Schiratti
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Automatic coronary artery calcium scoring from unenhanced-ECG-gated CT using deep learning
Nicolas Gogin
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Molecular Magnetic Resonance and Ultrasound Imaging of Tumor Angiogenesis
Marie Poirier-Quinot
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Ingrid Leguerney
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Automatic cervical lymphadenopathy segmentation from CT data using deep learning
Adele Courot
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Diana Lucia Farfan Cabrera
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Contrast-enhanced brain MRI synthesis with deep learning: key input modalities and asymptotic performance
Alexandre Bône
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Samy Ammari
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ISBI 2021 - International Symposium on Biomedical Imaging, Apr 2021, Nice / Virtual, France
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hal-03128023v1
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Lightweight U-Net for Lesion Segmentation in Ultrasound Images
Yingping Li
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Emilie Chouzenoux
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ISBI 2021 - IEEE International Symposium on Biomedical Imaging, Apr 2021, Nice / Virtual, France
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hal-03140737v2
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Study of the reliability of quantification methods of dynamic contrast-enhanced ultrasonography numerical modeling of blood flow in tumor microvascularization
Laure Boyer
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Ingrid Leguerney
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Prediction of the molecular status in non-small cell lung cancer based on metastatic pattern: A free webtool powered by artificial intelligence.
Benjamin Besse
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hal-03128125v1
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New method for quantification of intratumoral heterogeneity: a feasibility study on Ktrans maps from preclinical DCE-MRI
Charly Girot
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Andreas Volk
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Influence of magnetic field strength on magnetic resonance imaging radiomics features in brain imaging, an in vitro and in vivo study
Samy Ammari
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Stéphanie Pitre-Champagnat
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Can we trust the calculation of texture indices of CT images? A phantom study
Caroline Caramella
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Adrien Allorant
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Fanny Orlhac
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Toward a Standardization of Ultrasound Scanners for Dynamic Contrast-Enhanced Ultrasonography: Methodology and Phantoms
Stéphanie Pitre
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hal-03307576v1
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Can deep learning replace gadolinium in neuro-oncology?
Samy Ammari
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Alexandre Bône
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Corinne Balleyguier
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hal-03527628v1
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A Novel Microflow Phantom Dedicated to Ultrasound Microvascular Measurements
Virginie Grand-Perret
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Jean-René Jacquet
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Ingrid Leguerney
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Baya Benatsou
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Ultrasound Molecular Imaging of Renal Cell Carcinoma: VEGFR targeted therapy monitored with VEGFR1 and FSHR targeted microbubbles
Alexandre Ingels
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Ingrid Leguerney
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Jacques Irani
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hal-03128255v1
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Hyperprogressive disease during immunotherapy: an attempt to clarify different definitions
Baptiste Kas
,
Hugues Talbot
,
Roberto Ferrara
,
C Richard
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Benjamin Besse
et al.
2019
Preprints, Working Papers, ...
hal-02429762v1
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Pravastatin Reverses Established Radiation-Induced Cutaneous and Subcutaneous Fibrosis in Patients With Head and Neck Cancer: Results of the Biology-Driven Phase 2 Clinical Trial Pravacur
Céline Bourgier
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Anne Auperin
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Sofia Rivera
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Pierre Boisselier
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hal-02452478v1
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Guidelines for stage I to III melanoma [Actualisation des recommandations de prise en charge du mélanome stade I à III]
Bernard Guillot
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Sophie Dalac
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Marc Denis
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Alain Dupuy
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hal-01394771v1
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Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers
Laure Fournier
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Lena Costaridou
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Luc Bidaut
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Nicolas Michoux
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Frederic Lecouvet
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hal-03168841v1
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AI-based multi-modal integration (ScanCov scores) of clinical characteristics, lab tests and chest CTs improves COVID-19 outcome prediction of hospitalized patients
Nathalie Lassau
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Samy Ammari
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Emilie Chouzenoux
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Hugo Gortais
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Paul Herent
et al.
[Research Report] Inria Saclay Ile de France. 2020
Reports
hal-02586111v3
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Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients
Nathalie Lassau
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Samy Ammari
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Emilie Chouzenoux
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Hugo Gortais
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Paul Herent
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hal-03136018v1
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