Nicolas Brieu
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View article: 9P Benchmarking instance segmentation architectures for whole-cell segmentation in IHC-stained images: A multi-cancer study
9P Benchmarking instance segmentation architectures for whole-cell segmentation in IHC-stained images: A multi-cancer study Open
View article: 69eP Corrected grouped-lasso-based generative AI for the unsupervised extension of segmentation models to the analysis of translucent chromogenic IHC images
69eP Corrected grouped-lasso-based generative AI for the unsupervised extension of segmentation models to the analysis of translucent chromogenic IHC images Open
View article: 42P Controllable synthetic data generation for computational pathology via multimodal diffusion conditioning
42P Controllable synthetic data generation for computational pathology via multimodal diffusion conditioning Open
View article: 43P Few-shot quantitative continuous scoring through computational pathology foundation models
43P Few-shot quantitative continuous scoring through computational pathology foundation models Open
View article: Enhanced patient selection with quantitative continuous scoring of PD-L1 expression for IO treatment in metastatic NSCLC
Enhanced patient selection with quantitative continuous scoring of PD-L1 expression for IO treatment in metastatic NSCLC Open
Immune checkpoint inhibitors targeting PD-1/PD-L1 are approved for metastatic non-small-cell lung cancer treatment. In clinical practice, the treatment choice depends on visual scoring of PD-L1, which is subjective and semi-quantitative. I…
View article: Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion model
Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion model Open
Creating in-silico data with generative AI promises a cost-effective alternative to staining, imaging, and annotating whole slide images in computational pathology. Diffusion models are the state-of-the-art solution for generating in-silic…
View article: HER2 quantitative continuous scoring for accurate patient selection in HER2 negative trastuzumab deruxtecan treated breast cancer
HER2 quantitative continuous scoring for accurate patient selection in HER2 negative trastuzumab deruxtecan treated breast cancer Open
Many targeted cancer therapies rely on biomarkers assessed by scoring of immunohistochemically (IHC)-stained tissue, which is subjective, semiquantitative, and does not account for expression heterogeneity. We describe an image analysis-ba…
View article: Auxiliary CycleGAN-guidance for Task-Aware Domain Translation from Duplex to Monoplex IHC Images
Auxiliary CycleGAN-guidance for Task-Aware Domain Translation from Duplex to Monoplex IHC Images Open
Generative models enable the translation from a source image domain where readily trained models are available to a target domain unseen during training. While Cycle Generative Adversarial Networks (GANs) are well established, the associat…
View article: ReStainGAN: Leveraging IHC to IF Stain Domain Translation for in-silico Data Generation
ReStainGAN: Leveraging IHC to IF Stain Domain Translation for in-silico Data Generation Open
The creation of in-silico datasets can expand the utility of existing annotations to new domains with different staining patterns in computational pathology. As such, it has the potential to significantly lower the cost associated with bui…
View article: HER2 quantitative continuous scoring for accurate patient selection in HER2-negative trastuzumab deruxtecan–treated breast cancer
HER2 quantitative continuous scoring for accurate patient selection in HER2-negative trastuzumab deruxtecan–treated breast cancer Open
Many targeted cancer therapies rely on biomarkers assessed by scoring of immunohistochemically (IHC)-stained tissue, which is subjective, semiquantitative, and does not account for expression heterogeneity. We describe an image analysis-ba…
View article: 1505 Spatial profiling of the SCLC tumor microenvironment defined by high MHC-I expression reveals association with functionally relevant antigen presentation
1505 Spatial profiling of the SCLC tumor microenvironment defined by high MHC-I expression reveals association with functionally relevant antigen presentation Open
Background Small cell lung cancer (SCLC) is an aggressive and largely immune-cold cancer type, for which chemotherapy combined with Immuno-oncology (IO) therapies is providing benefit only in a subgroup of patients. SCLC is a highly hetero…
View article: 583 Quantitative computational assessment of PD-L1 enables robust patient selection for biomarker-informed anti-PD-L1 treatment of NSCLC patients
583 Quantitative computational assessment of PD-L1 enables robust patient selection for biomarker-informed anti-PD-L1 treatment of NSCLC patients Open
Background Immune checkpoint inhibitors (ICIs) targeting PD-1 or its ligand PD-L1 have shown clinical activity in patients with metastatic non-small cell lung cancer (mNSCLC). However, only subgroups of mNSCLC patients respond to ICI, whil…
View article: 579 Novel digital image approach of multiplex immunofluorescence based PD-L1 expression enables the stratification of advanced NSCLC patients treated with durvalumab
579 Novel digital image approach of multiplex immunofluorescence based PD-L1 expression enables the stratification of advanced NSCLC patients treated with durvalumab Open
Background Pathologist-based scoring of PD-L1 expression on tumor cells using IHC1 has shown clinical utility in predicting favorable overall survival in advanced non-small cell lung cancer (NSCLC) patients treated with anti-PD-…
View article: Stain Isolation-based Guidance for Improved Stain Translation
Stain Isolation-based Guidance for Improved Stain Translation Open
Unsupervised and unpaired domain translation using generative adversarial neural networks, and more precisely CycleGAN, is state of the art for the stain translation of histopathology images. It often, however, suffers from the presence of…
View article: Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images
Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images Open
We report the ability of two deep learning-based decision systems to stratify non-small cell lung cancer (NSCLC) patients treated with checkpoint inhibitor therapy into two distinct survival groups. Both systems analyze functional and morp…
View article: Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning
Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning Open
The clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes the assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quanti…
View article: FP07.02 Deep Learning Based Analysis of Multiplex IHC Accurately Interprets PD-L1 and Provides Prognostic Information in NSCLC
FP07.02 Deep Learning Based Analysis of Multiplex IHC Accurately Interprets PD-L1 and Provides Prognostic Information in NSCLC Open
View article: Identification of Immunological Features Enables Survival Prediction of Muscle-Invasive Bladder Cancer Patients Using Machine Learning
Identification of Immunological Features Enables Survival Prediction of Muscle-Invasive Bladder Cancer Patients Using Machine Learning Open
A bstract Clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quan…
View article: Graph-based description of tertiary lymphoid organs at single-cell level
Graph-based description of tertiary lymphoid organs at single-cell level Open
Our aim is to complement observer-dependent approaches of immune cell evaluation in microscopy images with reproducible measures for spatial composition of lymphocytic infiltrates. Analyzing such patterns of inflammation is becoming increa…
View article: Insights into the tumour immune microenvironment using tissue phenomics to drive cancer immunotherapy
Insights into the tumour immune microenvironment using tissue phenomics to drive cancer immunotherapy Open
View article: Prognostic immunoprofiling of muscle invasive bladder cancer (MIBC) patients in a multicentre setting
Prognostic immunoprofiling of muscle invasive bladder cancer (MIBC) patients in a multicentre setting Open
View article: Domain Adaptation-based Augmentation for Weakly Supervised Nuclei Detection
Domain Adaptation-based Augmentation for Weakly Supervised Nuclei Detection Open
The detection of nuclei is one of the most fundamental components of computational pathology. Current state-of-the-art methods are based on deep learning, with the prerequisite that extensive labeled datasets are available. The increasing …
View article: DASGAN -- Joint Domain Adaptation and Segmentation for the Analysis of Epithelial Regions in Histopathology PD-L1 Images
DASGAN -- Joint Domain Adaptation and Segmentation for the Analysis of Epithelial Regions in Histopathology PD-L1 Images Open
The analysis of the tumor environment on digital histopathology slides is becoming key for the understanding of the immune response against cancer, supporting the development of novel immuno-therapies. We introduce here a novel deep learni…
View article: Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma
Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma Open
View article: Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis
Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis Open
Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A …
View article: Augmenting TNM staging with machine learning-based immune profiling for improved prognosis prediction in muscle-invasive bladder cancer patients
Augmenting TNM staging with machine learning-based immune profiling for improved prognosis prediction in muscle-invasive bladder cancer patients Open
Background: Muscle-invasive bladder cancer (MIBC) is a highly aggressive disease whose clinical reporting is based on TNM staging. A more accurate and personalized prognosis could be achieved by profiling the immune contexture alongside cl…
View article: Front Matter: Volume 10581
Front Matter: Volume 10581 Open
identifier (CID) number is assigned to each article at the time of publication.Utilization of CIDs allows articles to
View article: Tissue Phenomics for prognostic biomarker discovery in low- and intermediate-risk prostate cancer
Tissue Phenomics for prognostic biomarker discovery in low- and intermediate-risk prostate cancer Open
View article: Context-based interpolation of coarse deep learning prediction maps for the segmentation of fine structures in immunofluorescence images
Context-based interpolation of coarse deep learning prediction maps for the segmentation of fine structures in immunofluorescence images Open
The automatic analysis of digital pathology images is becoming of increasing interest for the development of novel therapeutic drugs and of the associated companion diagnostic tests in oncology. A precise quantification of the tumor microe…
View article: In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium
In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium Open