N. Brieu

发表

Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis

Nicolas Brieu, Günter Schmidt, David J. Harrison, 2019, Scientific Reports.

Identification of Immunological Features Enables Survival Prediction of Muscle-Invasive Bladder Cancer Patients Using Machine Learning

Ognjen Arandjelovic, P. Caie, D. Harrison, 2020, bioRxiv.

Characterization of the hemodynamic response in the rat lumbar spinal cord using intrinsic optical imaging and laser speckle

Julien Cohen-Adad, Nicolas Brieu, Frederic Lesage, 2010, Journal of Neuroscience Methods.

PATHOLOGY INFORMATICS SUMMIT 2018

David E. Breen, William B. Lober, Hamid R. Tizhoosh, 2018, Journal of Pathology Informatics.

iDermatoPath – a novel software tool for mitosis detection in H&E‐stained tissue sections of malignant melanoma

A. Schäpe, J. Ring, N. Harder, 2017, Journal of the European Academy of Dermatology and Venereology : JEADV.

Abstract

David E. Breen, Alexis B. Carter, Pinky A. Bautista, 2000, European Neuropsychopharmacology.

Deep Semi Supervised Generative Learning for Automated Tumor Proportion Scoring on NSCLC Tissue Needle Biopsies

K. Steele, M. Rebelatto, G. Schmidt, 2018, Scientific Reports.

Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma

G. Madonna, G. Botti, P. Ascierto, 2019, Scientific Reports.

Tissue Phenomics for prognostic biomarker discovery in low- and intermediate-risk prostate cancer

Nathalie Harder, Nicolas Brieu, Mehmet Yigitsoy, 2018, Scientific Reports.

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016): part one

Charles J. Vaske, Rohan N. Borkar, Brian D. Kelly, 2016, Journal of Immunotherapy for Cancer.

In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium

C. Wemmert, G. Forestier, F. Feuerhake, 2016, Scientific Reports.

Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning

P. Caie, D. Harrison, G. Schmidt, 2021, Cancers.

Augmenting TNM staging with machine learning-based immune profiling for improved prognosis prediction in muscle-invasive bladder cancer patients.

P. Caie, C. Gavriel, N. Brieu, 2018, Annals of oncology : official journal of the European Society for Medical Oncology.

Context-based interpolation of coarse deep learning prediction maps for the segmentation of fine structures in immunofluorescence images

Nicolas Brieu, Günter Schmidt, David J. Harrison, 2018, Medical Imaging.

Learning size adaptive local maxima selection for robust nuclei detection in histopathology images

Nicolas Brieu, Günter Schmidt, G. Schmidt, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Slide-specific models for segmentation of differently stained digital histopathology whole slide images

Nicolas Brieu, Olivier Pauly, Johannes Zimmermann, 2016, SPIE Medical Imaging.

Optical imaging of vascular and metabolic responses in the lumbar spinal cord after T10 transection in rats

Nicolas Brieu, Frédéric Lesage, Simon Dubeau, 2009, Neuroscience Letters.

Graph-based description of tertiary lymphoid organs at single-cell level

Germain Forestier, Michael Meyer-Hermann, Nicolas Brieu, 2020, PLoS Comput. Biol..

Image-based Characterization of Thrombus Formation in Time-lapse DIC Microscopy: Segmentation under Low Contrast and Highly Dynamic Imaging Conditions

Nicolas Brieu, N. Brieu, Nicolas Brieu, 2012 .

583 Quantitative computational assessment of PD-L1 enables robust patient selection for biomarker-informed anti-PD-L1 treatment of NSCLC patients

H. Sade, P. Sontakke, Anatoliy Shumilov, 2022, Regular and Young Investigator Award Abstracts.

579 Novel digital image approach of multiplex immunofluorescence based PD-L1 expression enables the stratification of advanced NSCLC patients treated with durvalumab

A. Gupta, I. Achour, F. Segerer, 2022, Regular and Young Investigator Award Abstracts.

Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images

Nicolas Brieu, Günter Schmidt, Armin Meier, 2021, IEEE Transactions on Medical Imaging.

DASGAN - Joint Domain Adaptation and Segmentation for the Analysis of Epithelial Regions in Histopathology PD-L1 Images pdf

Nicolas Brieu, Ansh Kapil, Keith Steele, 2019, ArXiv.

Domain Adaptation-based Augmentation for Weakly Supervised Nuclei Detection pdf

Nicolas Brieu, Armin Meier, Guenter Schmidt, 2019, ArXiv.

Thrombus segmentation by texture dynamics from microscopic image sequences

Nassir Navab, Nicolas Brieu, Ana Cvejic, 2010, Medical Imaging.

A dynamic texture approach to semi-automatic thrombosis segmentation in in-vivo microscopic video-sequences

Nassir Navab, W. Ouwehand, D. Stemple, 2009 .

Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma

Nathalie Harder, Nicolas Brieu, Günter Schmidt, 2019, Scientific Reports.

A Graph-Based Digital Pathology Approach To Describe Lymphocyte Clustering Patterns After Renal Transplantation

F. Feuerhake, M. Meyer-Hermann, J. Bräsen, 2016 .

Image-based characterization of thrombus formation in time-lapse DIC microscopy

N. Navab, A. Cvejic, J. Serbanovic-Canic, 2012, Medical Image Anal..

Joint Thrombus and Vessel Segmentation Using Dynamic Texture Likelihoods and Shape Prior

Nassir Navab, Nicolas Brieu, Ana Cvejic, 2011, MICCAI.

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016): part one

Charles J. Vaske, Rohan N. Borkar, David M. Schauder, 2016, Journal for ImmunoTherapy of Cancer.