Palavras-chave:
- 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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| , , , , , and , (18F)-FDG PET/CT parameters to predict survival and recurrence in patients with locally advanced cervical cancer treated with chemoradiotherapy (2018), in: Cancer / Radiothérapie, 22:3(229-235) |
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| , , , , , , and , 18-FDG PET-CT parameters to predict survival and recurrence in cervical cancer patients treated with chemo-radiotherapy, in: European Society for Radiotherapy and Oncology, Vienna, 2017 |
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, , , and , 3-D Solid Texture Classification Using Locally-Oriented Wavelet Transforms (2017), in: IEEE Transactions on Image Processing, 26:4(1899-1910)
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| , , , , and , 3D Case–Based Retrieval for Interstitial Lung Diseases, in: MCBR-CDS 2009: Medical Content-based Retrieval for Clinical Decision Support, London, UK, páginas 39--48, Springer, 2010 |
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| , , and , 3D Lung Image Retrieval Using Localized Features, in: Medical Imaging 2011: Computer-Aided Diagnosis, Orlando, FL, USA, páginas 79632E, SPIE, 2011 |
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| , , , , , , and , 3D Riesz–wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), páginas 7909-7912, 2015 |
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, , , and , 3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis, 2020
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, , , , , , , and , 3D-Printed Iodine-Ink CT Phantom for Radiomics Feature Extraction - Advantages and Challenges (2023), in: Medical Physics, 50:9(5682-5697)
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, , , , , , , and , A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT (2016), in: IEEE Transactions on Medical Imaging, 35:12(2620-2630)
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| , , , , and , A Bispectral 3D UNet for Rotation Robustness in Medical Segmentation, in: The First Workshop on Topology- and Graph-Informed Imaging Informatics at MICCAI, páginas 43-54, Springer Nature Switzerland, 2024 |
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| , , , , , , and , A classification framework for lung tissue categorization, in: SPIE Medical Imaging, páginas 69190C-69190C-12, 2008 |
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| , , , and , A computerized score for the automated differentiation of usual interstitial pneumonia from regional volumetric texture analysis, in: Radiological Society of North America, scientific paper, 2014 |
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| , , , , , and , A framework for diagnosing interstitial lung diseases in HRCT : the TALISMAN project (2008), in: Swiss Medical Informatics, 64(17-20) |
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| , , , , , , , , , , , , , , and , A Global Taxonomy of Interpretable AI: Unifying the Terminology for the Technical and Social Sciences (2022), in: Artificial Intelligence Review, 56(3473–3504) |
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| , , and , A lung graph model for the classification of interstitial lung disease on CT images, in: SPIE Medical Imaging 2019: Computer-Aided Diagnosis, International Society for Optics and Photonics, páginas 869-876, SPIE, 2019 |
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| , , , , , and , A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT images, in: MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, páginas 58-68, 2016 |
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| , , and , A Medical Image Retrieval Application Using Grid Technologies to Speed Up Feature Extraction, in: ICT4Health, 2008 |
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| , , and , A Medical Image Retrieval Application Using Grid Technologies To Speed Up Feature Extraction in Medical Image Retrieval (2009), in: Philippine Journal of Information Technology |
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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 |
| , , , , and , A multimedia library of interstitial lung diseases at the University Hospitals of Geneva, in: Swiss Society of Radiology (SSR 2009), 2009 |
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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 , A PET-based nomogram for oropharyngeal cancers (2017), in: European Journal of Cancer, 75(222-230)
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| , , , , , , , , , , , , and , A radiomics-based analysis of functional dopaminergic scintigraphic imaging for the diagnosis of dementia with Lewy bodies (2025), in: Neurodegenerative Diseases |
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| , , , and , A semantic framework for the retrieval of similar radiological images based on medical annotations, in: IEEE International Conference on Image Processing, Paris, France, páginas 2241-2245, IEEE, 2014 |
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| , and , A web interface for 3D information retrieval with images from the lung, in: Medinfo 2010, Cape Town, South Africa, 2010 |
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| , , , and , Accessing the medical literature with content-based visual retrieval and text retrieval techniques., in: Proceedings of the Radiological Society of North America (RSNA), Chicago, Illinois, US, 2011 |
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| , Affine–invariant texture analysis and retrieval of 3D medical images with clinical context integration, University of Geneva, 2010 |
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| , , , , , , , , , , and , AI-based Prediction of Myocardium Viability Using [82Rb] PET/CT, 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, 2025 |
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| , , , , and , An easy setup for Parallel medical Image Processing: Using Taverna and ARC, in: Proceedings of HealthGrid 2009, páginas 41-50, 2009 |
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| , , , , , , and , An Exploration of Uncertainty Information for Segmentation Quality Assessment, in: SPIE Medical Imaging 2020: Image Processing, Houston, TX, USA, páginas 381-390, SPIE, 2020 |
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| , , and , Applications of Texture in Digital Pathology, in: 6th Annual Symposium of the Center for Biomedical Imaging at Stanford, Stanford, CA, USA, 2014 |
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, , , , , , , , and , Assessing radiomics feature stability with simulated CT acquisitions (2022), in: Scientific Reports, 12:1(4732)
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| , , , , , , and , Assessing Treatment Response in Triple Negative Breast Cancer from Quantitative Image Analysis in Perfusion MRI (2017), in: Journal of Medical Imaging, 5:1(5-10) |
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| , , , , , , , , and , Assessment of the stability and discriminative power of radiomics features in liver lesions using an anthropomorphic 3D-printed CT phantom, in: Scientific session SGR-SSR, 2021 |
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| , , , and , Asymmetric margin support vector machines for lung tissue classification, in: IEEE International Joint Conference on Neural Networks (IJCNN), Barcelona, Spain, páginas 1--8, 2010 |
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, , and , Automated Classification of Brain Tumor Type in Whole-Slide Digital Pathology Images Using Local Representative Tiles (2016), in: Medical Image Analysis, 30(60-71)
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, , , , , and , Automated Classification of Usual Interstitial Pneumonia using Regional Volumetric Texture Analysis in High-Resolution CT (2015), in: Investigative Radiology, 50:4(261-267)
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, , and , Automated Object Extraction for Medical Image Retrieval Using the Insight Toolkit (ITK)., in: AIRS, páginas 476-488, 2006
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| , , , , , , , , and , Automatic Detection and Multi-Component Segmentation of Brain Metastases in Longitudinal MRI (2024), in: Nature Scientic Reports, 14:1(1-10) |
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, , , , , , , , , , and , Automatic Head and Neck Tumor Segmentation and Outcome Prediction Relying on FDG-PET/CT Images: Findings from the Second Edition of the HECKTOR Challenge (2023), in: Medical Image Analysis, 90:1(102972)
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| , , , , , and , Automatic rib fracture detection on postmortem CT data using deep learning (2025), in: International Journal of Legal Medicine |
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| , , , , , , , and , Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans, in: Medical Imaging with Deep Learning, Montréal, Canada, 2020 |
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| , , , , and , Benefits of texture analysis of dual energy CT for computer-aided pulmonary embolism detection, in: The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Osaka, Japan, páginas 3973-3976, 2013 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Biomedical image analysis competitions: The state of current participation practice (2022), in: arXiv |
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| , and , Biomedical Texture Analysis: Fundamentals, Applications and Tools, Elsevier, Elsevier-MICCAI Society Book series, 2017 |
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| and , Biomedical Texture Operators and Aggregation Functions: A Methodological Review and User’s Guide, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, páginas 55-94, Elsevier, 2017 |
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| , , , and , Building a Community Grid for Medical Image Analysis inside a Hospital, a Case Study, in: Medical imaging on grids: achievements and perspectives (Grid Workshop at MICCAI 2008), páginas 3-12, 2008 |
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| , , , , and , Building a library of annotated pulmonary CT cases for diagnostic aid, in: Swiss conference on medical informatics (SSIM 2006), 2006 |
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