Keywords:
- https://publications.hevs.ch/index.php/keywords/single/197
- 3D information retrieval
- 3D texture
- AI
- ARC
- artificial intelligence
- Atlas
- Automatic segmentation
- Benchmarking
- big data
- Biological tissue
- 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
- cs.CV
- data mining
- Desktop Grid
- 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
- Lesion detection
- Lesion segmentation
- lung
- Lung image
- Lung image analysis
- Lung image retrieval
- lung segmentation
- lung tissue classification
- machine learning
- Machine Learning (cs.LG)
- 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
- nosocomial infection
- oncology
- organ segmentation
- Oropharynx
- radiomics
- retrieval
- Riesz
- Riesz transform
- scalability
- Security
- signal processing
- social interaction
- support vector machines
- Systematic Review
- Taverna
- technologism
- test collection
- test collection creation including signals and images
- texture analysis
- texture classification
- user interface
- user interfaces
- User testing and task analysis
- virtualization
- visceral-project
- visual feature extraction
- visual inforamtion retrieval
- visual information retrieval
- wavelet
- wavelets
- Yearbook
Publications of Adrien Depeursinge sorted by title
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| Head and Neck Tumor Segmentation, Springer International Publishing, 2021 |
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| Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2022 |
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| , , and , Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2023 |
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| , , , , , , and , HEad and neCK TumOR segmentation and outcome prediction using AI: lessons from three consecutive years of the HECKTOR challenge, in: European Head and Neck Society (EHNS) on Artificial Intelligence (AI) in Head & Neck Oncology, Lausanne and virtual, 2023 |
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| , , , , , , , and , HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022 |
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, , , , , , , , , , , , , , , , , , , , , , , , , and , Head and Neck Tumor Segmentation in PET/CT: The HECKTOR Challenge (2022), in: Medical Image Analysis, 77(102336)
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| , , and , Hierarchic Anatomical Structure Segmentation Guided by Spatial Correlations (AnatSeg-Gspac): VISCERAL Anatomy3, in: Proceedings of the VISCERAL Anatomy Grand Challenge at the 2015 IEEE ISBI, pages 22-26, CEUR-WS, 2015 |
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, and , Hierarchical classification using a frequency-based weighting and simple visual features (2008), in: Pattern Recognition Letters, 29:15(2011-2017)
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| , , , , , , , , , , and , Holistic Classification of CT Attenuation Patterns for Interstitial Lung Diseases via Deep Convolutional Neural Networks, in: 1st Workshop on Deep Learning in Medical Image Analysis, Münich, Germany, pages 41-48, 2015 |
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| , , , , , , , and , Holographic visualisation and interaction of fused CT, PET and MRI volumetric medical imaging data using dedicated remote GPGPU ray casting, in: Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation, pages 102-110, Springer International Publishing, 2018 |
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| , , , , and , How clinical information systems can support life science research (2008), in: Swiss Medical Informatics, 64(21-24) |
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, , , , , , and , How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review (2023), in: NeuroImage: Clinical, 39(103491)
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| , , , , , , and , How to find the best radiomics features for prediction of overall survival in SBRT for hepatocellular carcinoma?, in: European SocieTy for Radiotherapy & Oncology, 2019 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Identification of paramagnetic rim lesions using conventional MRI - a deep learning approach, in: 39th Congress Of The European Committee For Treatment And Research In Multiple Sclerosis (ECTRIMS), 2023 |
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| , , , , and , Image-based diagnostic aid for interstitial lung disease with secondary data integration, in: SPIE Medical Imaging, 2007 |
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| , , , , , , and , Impact of a Gaussian filter applied to post-reconstruction PET images on radiomic features to predict complete pathological response in breast cancer (2020), in: Journal of Nuclear Medicine, 61:supplement 1(606--606) |
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| , , , , , , and , Impact of a Gaussian filter applied to post-reconstruction PET on radiomic features in assessing tumor heterogeneity in breast cancer. (2020), in: Journal of Nuclear Medicine, 61:supplement 1(612--612) |
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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 |
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| , , , , , , , , , , , and , Impact of deep learning segmentation methods on the robustness of MR glioblastoma radiomics, in: 2022 Annual Meeting of the European Society of Radiation Oncology (ESTRO), 2022 |
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| , , , , , , , and , Influence of CT Scanners on Radiomics Features in Abdominal CT: A Multicenter Phantom Study, in: European Congress of Radiology, 2024 |
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| , and , Information Fusion for Combining Visual and Textual Image Retrieval, in: 20th IEEE International Conference on Pattern Recognition (ICPR), Istanbul, Turkey, pages 1590--1593, 2010 |
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| , , , , , , , and , Instance-level explanations in multiple sclerosis lesion segmentation: a novel localized saliency map, in: ISMRM 2024, 2024 |
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| , , , , , , , and , Instance-level quantitative saliency in multiple sclerosis lesion segmentation (2026), in: Nature Scientific Reports |
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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 , Integrating radiomics into holomics for personalised oncology: from algorithms to bedside (2020), in: European Radiology Experimental, 4(11) |
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| , , , , , , , , , and , Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis, 2024 |
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| , , , and , Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging, in: Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2020, 2020 |
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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 , Is tumor heterogeneity quantified by 3D texture analysis of MRI able to predict non-response to NAC in breast cancer?, in: European Society for Magnetic Resonance in Medicine and Biology, 2016 |
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| , , , , and , KnowARC: Enabling Grid Networks for the Biomedical Research Community, in: Healthgrid 2007, pages 261-268, 2007 |
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| and , La recherche d’images en plusieurs dimensions (2011), in: Market/IBCom |
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| , and , Learning Cross-Protocol Radiomics and Deep Feature Standardization from CT Images of Texture Phantoms, in: SPIE Medical Imaging 2019, International Society for Optics and Photonics, pages 109-116, SPIE, 2019 |
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| , , , , , , , , and , Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Convolutional Neural Networks, 2025 |
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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 , Local Rotation Invariance in 3D CNNs (2020), in: Medical Image Analysis, 65(101756)
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| , , , , , , , , and , Locoregional radiogenomic models to capture gene expression heterogeneity in glioblastoma (2018), in: biorXiv |
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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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| , , , , , , , , , 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 , Lung Texture Classification Using Locally–Oriented Riesz Components, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011, Toronto, Canada, pages 231-238, Springer Berlin / Heidelberg, 2011 |
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| , , and , Lung Tissue Analysis Using Isotropic Polyharmonic B-Spline Wavelets, in: MICCAI 2008 Workshop on Pulmonary Image Analysis, pages 125-134, 2008 |
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| , , , , and , Lung Tissue Classification in HRCT data Integrating the Clinical Context, in: 21th IEEE Symposium on Computer-Based Medical Systems (CBMS), pages 542-547, 2008 |
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| , , , , , and , Lung Tissue Classification Using Wavelet Frames, in: Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2007 |
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| , , , , and , Making sense of radiomics: Insights on human-AI collaboration in medical interaction from an observational user study (2024), in: Frontiers in Communication, 8 |
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| , , , , , and , Measuring the effectiveness of hospital-acquired infection prevention, in: Medinfo 2010, Cape Town, South Africa, pages 764-768, IOS Press, 2010 |
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| and , Medical visual information retrieval based on multi-dimensional texture modeling, in: Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11), pages 127-129, 2011 |
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| , , , and , Medical visual information retrieval: from techniques to applications and evaluation, in: The 2nd International Conference on Advanced Information and Telemedicine Technologies for Health (AITTH 2008), pages 77-81, 2008 |
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