Palavras-chave:
- https://publications.hevs.ch/index.php/keywords/single/197
- 3D imaging
- 3D information retrieval
- 3D texture
- 82Rb PET/CT
- AI
- ARC
- artificial intelligence
- Atlas
- Automatic segmentation
- Benchmarking
- big data
- Biological tissue
- Brain
- CAD
- case-based retrieval
- Challenge
- Classification
- clinical data
- clinical data analysis
- clinical workflows
- Computer Vision and Pattern Recognition (cs.CV)
- computer-aided diagnosis
- computerised tomography
- computing infrastructures
- Content-based image retrieval
- conversation analysis
- Cortical lesions
- Cox Model
- cs.CV
- data mining
- Deep convolutional neural network
- Deep Learning
- Desktop Grid
- detection
- Discrete wavelet transform
- eHealth
- Epilepsy
- ethnomethodology
- evaluation
- exoticism
- feature extraction
- FOS: Computer and information sciences
- fracture retrieval
- Grid
- Hadoop
- head and neck cancer
- Healthcare
- HealthGrid
- High-resolution lung CT
- Hospital
- Human-Centered Computing
- image acquisition
- image analysis
- image classif
- image classification
- Image databases
- image processing
- image retrieval
- image storage
- ImageCLEF
- information fusion
- information retrieval
- information retrieval evaluation
- information retrieval literature
- Information Systems
- Infrastructures for computation
- interstitial lung diseases
- Left Ventricle Segmentation
- Lesion detection
- Lesion segmentation
- lung
- Lung image
- Lung image analysis
- Lung image retrieval
- lung segmentation
- lung tissue classification
- machine learning
- Machine Learning (cs.LG)
- Magnetic resonance imaging
- MapReduce
- medical image analysis
- Medical image analysis and retrieval
- medical image processing
- Medical image retrieval
- medical imaging
- Medical informatics
- Medical information retrieval
- mentalism
- mobile devices
- mobile information retrieval
- MRI
- multi-atlas based segmentation
- multidimensional image data analysis
- multimedia library
- Multimodal information retrieval and information fusion
- Multiple sclerosis
- Myocardial Blood Flow
- nosocomial infection
- oncology
- organ segmentation
- Oropharynx
- radiomics
- retrieval
- Riesz
- Riesz transform
- Rubidium PET
- scalability
- Security
- segmentation
- signal processing
- social interaction
- support vector machines
- Systematic Review
- Taverna
- technologism
- test collection
- test collection creation including signals and images
- texture analysis
- texture classification
- Transmural Perfusion
- Trustworthy AI
- user interface
- user interfaces
- User testing and task analysis
- virtualization
- visceral-project
- visual feature extraction
- visual inforamtion retrieval
- visual information retrieval
- wavelet
- wavelets
- Yearbook
Publicações de Adrien Depeursinge ordenado por recente
| , , , , , , , , , , and , MSXplain Web – A Platform for AI-based Multiple Sclerosis Lesion Segmentation, Localization, and Reporting in MRI, 2026 |
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| , , , , , , and , The QuantImage v2 Online Platform for Interactive Radiomics AI Education and Advanced Model Interpretation, 2026 |
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| , , , , , , , and , Multi-depth Rubidium PET Graph Neural Network for Major Adverse Cardiac Event Prediction, in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2026, 2026 |
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| , , , , , and , Dynamic Modeling of Brain Metastasis Response with Multitask Temporal Learning, in: Medical Image AI in Radiation Therapy (MIART) at MICCAI 2026, 2026 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , HEad and neCK TumOR (HECKTOR) 2025: Benchmark of Segmentation, Diagnosis, and Prognosis in Multimodal PET/CT, 2026 |
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| , , , , , , , , , , , and , Foundation Model–Enhanced Classification of Paramagnetic Rim Lesions in Multiple Sclerosis, MSToronto2026 – 10th Joint ACTRIMS-ECTRIMS Meeting, 2026 |
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| , , , , , , and , The QuantImage v2 Online Platform for Interactive Radiomics AI Education and Advanced Model Interpretation, Swiss Congress of Radiology (SCR), 2026 |
| , , , , , , , and , AI-Driven Volumetric 17-Segment Myocardial Blood Flow Characterisation Using [82Rb] PET/CT, ePoster at the Annual Congress of the European Association of Nuclear Medicine (EANM), 2026 |
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| , , , , , , , , , and , Fully Automatic Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Learning, Annual Swiss Congress of Radiology (SCR), 2026 |
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| , , , , , , , and , Transmural myocardial blood flow characterization with AI-enabled parametric mapping improves prediction of major adverse cardiac events, Annual Congress of the American Society of Nuclear Cardiology (ASNC), 2026 |
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| , , , , and , Prognostic value of PSMA theranostic imaging in mCRPC using a fully automatic AI pipeline, Annual Congress of the European Association of Nuclear Medicine (EANM), 2026 |
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| , , , , , , , , , , and , Contribution of quantitative I-123-ioflupane SPECT/CT to the differential diagnosis of dementia with lewy bodies (2026), in: European Journal of Nuclear Medicine and Molecular Imaging, 53:4(2777--2785) |
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| , , , , , , , , , , , , , , , , , , and , A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosis (2026), in: NeuroImage: Clinical, 50(104007) |
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| , , , and , Post-surgical detection of glioma recurrence using MRI radiomics (2026), in: Neuro-Oncology Advances, 8:1(vdag143) |
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| , , , , , , , , and , Fully Automatic Left Ventricle Segmentation in 82Rb PET/CT Using a Semi-Supervised nnU-Net (2026), in: EJNMMI Research |
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| , , , , , , , , , , , and , Multi-Method eXplainability for Similarity Assessment in AI-Denoised PET Imaging, in: 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), páginas 1-4, 2026 |
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| , , , , , and , Automatic rib fracture detection on postmortem CT data using deep learning (2026), in: International Journal of Legal Medicine, 140:2(857-866) |
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| , , , , , and , LEXU: Learning from Expert Disagreement for Single-Pass Uncertainty Estimation in Medical Image Segmentation, in: International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2025 |
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| , , , , , , , , , , , , and , Deep learning [18F]-FDG-PET/CT‑based algorithm for tumor burden estimation in metastatic melanoma patients under immunotherapy (2026), in: Clinical and Translational Radiation Oncology, 56(101063) |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , A Multimodal and Multi-centric Head and Neck Cancer Dataset for Tumor Segmentation and Outcome Prediction (2025) |
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| , and , Interpretable Regime Trajectories via Generative Graph State-Space Models, in: New Perspectives in Graph Machine Learning NPGML at NeurIPS 2025, 2025 |
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| , , , , , , , , , and , RDTA-08 MULTI-SEQUENTIAL STEREOTACTIC RADIOSURGERY (SRS) FOR BRAIN METASTASES: 10-YEAR EXPERIENCE FROM THE CHUV (LAUSANNE, SWITZERLAND) BRAIN METASTASIS CLINIC (2025), in: Neuro-Oncology Advances, 7:Supplement_2(ii26-ii26) |
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| , , , , , , , , , , , , , , , and , Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction Errors, 2025 |
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| , , , , , , , , , , , and , Impact of CT dose on AI performance: A comparison of radiomics, deep, and foundation models in a multi-centric anthropomorphic phantom study (2026), in: Medical Physics, 53:3(e70374) |
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, , , , , , , , , , , , , , , , , , , , and , The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information, 2025
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| , , , , , , , , , , and , Contribution of Quantitative I-123-ioflupane SPECT/CT to the Differential Diagnosis of Dementia with Lewy Bodies (2025), in: European Journal of Nuclear Medicine and Molecular Imaging |
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| , , , , , , , , , , , , and , A multi-modal deep learning network for the classification of paramagnetic rim and remyelinated lesions in multiple sclerosis (2026), in: Multiple Sclerosis Journal, 32:6(13524585261421491) |
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| , , , , , , , , and , Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Convolutional Neural Networks, Annual Congress of the European Association of Nuclear Medicine (EANM), 2025 |
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| , , , , , , , , , , and , AI-based Prediction of Myocardium Viability Using [82Rb] PET/CT, Annual Congress of the European Association of Nuclear Medicine (EANM), 2025 |
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| , , , , , , and , AI-based response assessment and prediction in longitudinal imaging for brain metastases treated with stereotactic radiosurgery, in: Learning with Longitudinal Medical Images and Data at MICCAI 2025, páginas 102-112, Springer Nature Switzerland, 2026 |
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| , , , and , Teaching Radiomics through an Interactive Platform: A Qualitative Study on the Use of QuantImage in Medical Education, European Society of Medical Imaging Informatics (EuSoMII), 2025 |
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| , , , , , , , , , , , , and , A radiomics-based analysis of functional dopaminergic scintigraphic imaging for the diagnosis of dementia with Lewy bodies (2026), in: Neurodegenerative Diseases, 26:1 |
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| , , , , , , , , , , , and , Deep learning PET/CT-based algorithm for estimating tumor burden in metastatic melanoma patients under immunotherapy, in: ESTRO 2025, 2025 |
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| , , , and , Unraveling AI imaginaries in radiomics: Beyond exoticism, mentalism, and technologism, 10th STS Italia Conference - Technoscience for Good: Designing, Caring, and Reconfiguring, 2025 |
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| , , , , , , , and , Integrating MRI and PET/CT Radiomics for Enhanced Survival Prediction in Esophageal Cancer, in: European Congress of Radiology, 2025 |
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| , , , , , , , , and , Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation (2025), in: Computers in Biology and Medicine |
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| , , , , , , , , , and , Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis, 2024 |
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| , , , , , , and , MRI and CT radiomics for the diagnosis of acute pancreatitis (2025), in: European Journal of Radiology Open, 14 |
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| , , , , , , , , , , and , Deep-PRL: a deep learning network for the identification of paramagnetic rim lesions in multiple sclerosis, in: ISMRM 2025, 2025 |
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| , , , , , , , , , and , Lung lesion detectability on images obtained from decimated and CNN-based denoised [18F]-FDG PET/CT scan: An observer-based study for lung-cancer screening (2025), in: European Journal of Nuclear Medicine and Molecular Imaging |
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| , , , , , , , , , , , and , Explainability in automatic Paramagnetic Rim Lesion classification, in: 40th Congress Of The European Committee For Treatment And Research In Multiple Sclerosis (ECTRIMS), 2024 |
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| , , , , , , and , Exploiting XAI maps to improve MS lesion segmentation and detection in MRI, in: Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI, 2025 |
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| , , , , , , and , Evaluation of PaIRe PET/CT segmentation software as cancerous lesion contouring tool in fully- automated annotation workflows for image-based research studies, in: Annual Congress of the European Association of Nuclear Medicine, 2023 |
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| , , , , , , , , , and , Lung lesion detectability on decimated and CNN-based denoised 18F-FDG PET/CT, in: Swiss Congress of Radiology, 2024 |
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