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 , Comparative Performance Analysis of State-of-the-Art Classification Algorithms Applied to Lung Tissue Categorization (2010), in: Journal of Digital Imaging, 23:1(18-30)
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| , , , , and , Comparing 18-FDG PET 3D texture attributes for the prediction of survival and recurrence in oropharyngeal cancers treated with radiotherapy, in: Workshop on the Prediction and Modeling of response to Molecular and External Beam Radiotherapies, Le Bono, France, 2017 |
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| , , , , , , , , , and , Comparing Stability and Discriminatory Power of Handcrafted Versus Deep Radiomics: A 3D-Printed Anthropomorphic Phantom Study, in: 12th IEEE European Workshop on Visual Information Processing, pages 62-66, 2024 |
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| , , , , , , , , , and , Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction (2024), in: Nature Scientific Reports, 14:9644 |
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| , , , , , and , Comparison of feature selection in radiomics for the prediction of overall survival after radiotherapy for hepatocellular carcinoma, in: IEEE Engineering in Medicine and Biology Conference, 2020 |
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| , , , , , , , and , Comparison of MR preprocessing strategies and sequences for radiomics-based MGMT prediction, in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (MICCAI/BrainLes 2021), Cham, pages 367–380, Springer International Publishing, 2022 |
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| , , , , and , Computer-aided diagnostic for interstitial lung diseases in HRCT: the TALISMAN project, in: Swiss Conference on Medical Informatics, 2008 |
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| , , , and , Computerized assistance for diagnosing interstitial lung disease in emergency radiology, in: Proceedings of the annual congress of the Swiss society of radiology, 2007 |
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| , , and , Consistency of Scale Covariance in Internal Representations of CNNs, in: Irish Machine Vision and Image Processing Conference, 2020 |
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| , , , , , and , Content-based image retrieval from a database of fracture images, in: Medical Imaging 2007: PACS and Imaging Informatics, pages 65160H, 2007 |
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| , , , , and , Content-based retrieval and analysis of HRCT images from patients with interstitial lung diseases, in: HUG Research Day 2009, 2009 |
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| , , , , , and , Content-based retrieval and analysis of HRCT images from patients with interstitial lung diseases: a comprehesive diagnostic aid framework, in: Computer Assited Radiology and Surgery (CARS) 2010, Geneva, Switzerland, 2010 |
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| , , , , , and , Deep learning classifier for MGMT promoter methylation status in glioblastoma cancer, in: 2022 Annual Meeting of the European Society of Radiation Oncology (ESTRO), 2022 |
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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 , Design implications of repurposing a radiomics research platform for education: The case of QuantImage v2, 2024 |
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| , , , , and , Design of a Decentralized Reusable Research Database Architecture to Support Data Acquisition in Large Research Projects, in: MedInfo 2007, pages 325-329, 2007 |
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| , , and , Efficient and fully automatic segmentation of the lungs in CT volumes, in: Proceedings of the VISCERAL Anatomy Grand Challenge at the 2015 IEEE ISBI, New York, USA, pages 31-35, CEUR-WS, 2015 |
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| , , and , Enhanced visualization of pulmonary perfusion in 4D Dual Energy CT images, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA, pages 6710-6713, 2014 |
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| , , , and , Epileptogenic lesion quantification in MRI using contralateral 3D texture comparisons, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, pages 353-360, Springer Berlin Heidelberg, 2013 |
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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 , Evaluation of the Prognostic Value of FDG PET/CT Parameters for Patients with Surgically Treated Head and Neck Cancer: A Systematic Review (2020), in: JAMA Otolaryngology - Head and Neck Surgery, 146:5(471-479)
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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, 2024 |
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, , , and , Exploring local rotation invariance in 3D CNNs with steerable filters, in: Medical Imaging with Deep Learning, pages 15-26, Proceedings of Machine Learning Research, 2019
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| , and , Faciliter l'utilisation des grilles de calcul dans le domaine biomédical: Le projet KnowARC, in: Journées francophones d'informatique médicale, 2007 |
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| , , and , Fast Rotational Sparse Coding (2018)(arXiv:1806.04374) |
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, , , , , , , , , and , FDG-PET/CT-based prognostic survival model after surgery for head and neck cancer (2022), in: Journal of Nuclear Medicine, 63:1
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| , , , , , , , and , FLAIR vs MPRAGE contribution to white matter lesion automatic segmentation in MS using localized saliency maps, in: Bern Interpretable AI Symposium (BIAS), 2023 |
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| , , , , , and , Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, pages 59-68, Springer LNCS, 2021 |
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| , and , Fundamentals of Texture Processing for Biomedical Image Analysis: A General Definition and Problem Formulation, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 1-27, Elsevier, 2017 |
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, , and , Fusing Learned Representations from Riesz and Deep CNNs for Lung Tissue Classification (2019), in: Medical Image Analysis, 56(172-183)
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| , , , , , and , Fusing visual and clinical information for lung tissue classification in high-resolution computed tomography (2010), in: Artificial Intelligence in Medicine, 50:1(13--21) |
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| and , Fusion Techniques for Combining Textual and Visual Information Retrieval, in: ImageCLEF, pages 95-114, Springer Berlin Heidelberg, 2010 |
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| , , , , and , GPU-Accelerated Texture Analysis Using Steerable Riesz Wavelets, in: 24th IEEE Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Heraklion Crete, Greece, pages 431--434, 2016 |
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| , , , and , Grid Computing Inside Hospitals using Virtualization Technology: A secure solution for heavy computing tasks, in: Annual Conference for Swiss Society of Medical Informatics, Bern, Switzerland, 2009 |
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| , , , and , Grid Computing Inside Hospitals using Virtualization Technology: A secure solution for heavy computing tasks, in: HUG Research Day 2009, 2009 |
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| , , , and , Guide for radiologists and nuclear medicine physicians for a standardized radiomics analysis, in: Swiss Congress of Radiology (SCR) 2023, 2023 |
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H
| 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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