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
- data mining
- Desktop Grid
- Discrete wavelet transform
- eHealth
- Epilepsy
- ethnomethodology
- evaluation
- feature extraction
- FOS: Computer and information sciences
- fracture retrieval
- Grid
- Hadoop
- head and neck cancer
- HealthGrid
- High-resolution lung CT
- Hospital
- 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
- 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
- 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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| , , , , , , , 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 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 |
| , , , , , , , and , Instance-level quantitative saliency in multiple sclerosis lesion segmentation (2024), in: arxiv |
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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 , 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 , 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 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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| , , , , and , Medical Visual Information Retrieval: State of the Art and Challenges Ahead, in: Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, pages 683-686, 2007 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision, 2023 |
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, , , , , and , Metabolic Tumor Volume and Total Lesion Glycolysis in Oropharyngeal Cancer treated with definitive radiotherapy: Which threshold is the best predictor of local control ? (2017), in: Clinical Nuclear Medicine, 42:6(e281–e285)
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| , , , , and , Minimal Set of Attributes Required to Report Hospital-Acquired Infection Cases, in: IDAMAP 2008 - Workshop on Intelligent Data Analysis in Biomedicine and Pharmacology, Washington DC, pages 23-28, 2008 |
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| , and , Mobile image upload for radiology, in: Studies in Health Technology and Informatics, Copenhagen, Denmark, pages 1003, 2013 |
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| , , and , Mobile Medical Image Retrieval, in: Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications, Orlando, FL, USA, pages 79670G, SPIE, 2011 |
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, , and , Mobile Medical Visual Information Retrieval (2012), in: IEEE Transactions on Information Technology in BioMedicine, 16:1(53-61)
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| , , , , , , and , MRI and CT radiomics for the diagnosis of acute pancreatitis (2025), in: European Journal of Radiology Open |
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| , , , and , Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectral U-Net, in: Medical Imaging with Deep Learning, 2022 |
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| , Multi-Scale and Multi-Directional Biomedical Texture Analysis: Finding the Needle in the Haystack, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 29-53, Elsevier, 2017 |
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| , , , , , and , Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer, in: 4th Workshop on PRedictive Intelligence in MEdicine, pages 147-156, Springer LNCS, 2021 |
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| , and , Multidimensional Texture Analysis for Improved Prediction of Ultrasound Liver Tumor Response to Chemotherapy Treatment, in: Medical Image Computing and Computer-Assisted Interventions (MICCAI), pages 619--626, Springer International Publishing, 2016 |
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| , , and , Multiscale Lung Texture Signature Learning Using The Riesz Transform, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012, Nice, France, pages 517-524, Springer Berlin / Heidelberg, 2012 |
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, , , , and , Near–Affine–Invariant Texture Learning for Lung Tissue Analysis Using Isotropic Wavelet Frames (2012), in: IEEE Transactions on Information Technology in BioMedicine, 16:4(665-675)
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| , and , Neural Network Training for Cross-Protocol Radiomic Feature Standardization in Computed Tomography (2019), in: Journal of Medical Imaging, 6:3(024008) |
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