Institute of Informatics (II)
Onderwerp: MedGIFT
Alle publicaties voor onderwerp "MedGIFT" gesorteerd op titel
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| , , , , , , en , 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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, , , en , Exploring local rotation invariance in 3D CNNs with steerable filters, in: Medical Imaging with Deep Learning, pagina's 15-26, Proceedings of Machine Learning Research, 2019
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| , en , Extensions to the Multimedia Retrieval Markup Language - A Communication Protocol for Content-Based Multimedia Indexing, in: Proceedings of the Internation Workshop on Content-Based Multimedia Indexing (CBMI 2003), pagina's 173-180, 2003 |
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| , , en , Facilitating Medical Information Search using Google Glass connected to a Content-based Medical Image Retrieval System, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA, 2014 |
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| , en , 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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| , , , , , en , Fast Content-based Visual Retrieval of Radiology Cases in Hospital Systems, in: RSNA, Chicago, IL, USA, 2012 |
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| , , en , Fast Rotational Sparse Coding (2018)(arXiv:1806.04374) |
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| , , , , en , Fast search for radiology cases in hospital systems via content-based image retrieval, in: European Congress of Radiology, Vienna, Austria, 2013 |
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| en , Finding seed points for organ segmentation using example annotations, in: SPIE Medical Imaging 2014, San Diego, CA, USA, 2014 |
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| , , , , , , , en , 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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en , Forschungsanwendungen in der digitalen Radiologie: Big data und Co. (2016), in: Der Radiologe
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| , , , , , , , en , From Genes to Personalized Healthcare: Grid Solutions for the Life Sciencens, IOS Press, Studies in Health Technology and Informatics, deel 126, 2007 |
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| , , , en , From NinaPro to MeganePro towards the natural control of myoelectric prosthetic hands, in: Cybathlon Symposium, Zurich, Switzerland, 2016 |
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| , , , , , en , Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, pagina's 59-68, Springer LNCS, 2021 |
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| , , , , , , , , en , Fully Automatic Left Ventricle Segmentation in 82Rb PET/CT Using a Semi-Supervised nnU-Net (2026), in: EJNMMI Research |
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| , , , , , , , , , en , Fully Automatic Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Learning, Annual Swiss Congress of Radiology (SCR), 2026 |
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| , en , Fundamentals of Texture Processing for Biomedical Image Analysis: A General Definition and Problem Formulation, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pagina's 1-27, Elsevier, 2017 |
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, , en , Fusing Learned Representations from Riesz and Deep CNNs for Lung Tissue Classification (2019), in: Medical Image Analysis, 56(172-183)
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| , , , , , en , 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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| en , Fusion Techniques for Combining Textual and Visual Information Retrieval, in: ImageCLEF, pagina's 95-114, Springer Berlin Heidelberg, 2010 |
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| en , Fusion Techniques in Biomedical Information Retrieval, Springer, 2014 |
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, , , , , , , , , , , , , en , General Overview of ImageCLEF at the CLEF 2015 Labs, in: CLEF 2015 Proceedings, 2015
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| , , , , , , , , , , , , , , , en , General Overview of ImageCLEF at the CLEF 2016 Labs, in: CLEF Proceedings, Springer, 2016 |
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| , , en , Gesture interaction for content--based medical image retrieval, in: ACM ICMR, Glasgow, UK, 2014 |
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| , , , , en , GPU-Accelerated Texture Analysis Using Steerable Riesz Wavelets, in: 24th IEEE Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Heraklion Crete, Greece, pagina's 431--434, 2016 |
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| , , en , Grid Computing at the University Hospitals of Geneva, in: Proceedings of the 1st healthGrid conference, pagina's 264-276, 2003 |
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| , , , en , Grid Computing Inside Hospitals using Virtualization Technology: A secure solution for heavy computing tasks, in: HUG Research Day 2009, 2009 |
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| , , , en , 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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| , , , , , en , Grid Data Management for Liquid Time Projection Chamber Data Analysis, in: EGI user forum, Vilnius, Lithuania, 2011 |
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| en , Ground truth generation in medical imaging: A crowdsourcing based iterative approach, in: Workshop on Crowdsourcing for Multimedia, ACM Multimedia, Nara, Japan, 2012 |
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| , , en , Harnessing the Scientific Data Produced by the Experimental Evaluation of Search Engines and Information Access Systems, Elsevier Grand Challenge, 2011 |
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| Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2022 |
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| , , , , , , , en , HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022 |
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, , , , , , , , , , , , , , , , , , , , , , , , , en , Head and Neck Tumor Segmentation in PET/CT: The HECKTOR Challenge (2022), in: Medical Image Analysis, 77(102336)
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| , , , , en , Health care professionals' image use and search behaviour, in: Proceedings of the Medical Informatics Europe Conference (MIE 2006), pagina's 24-32, 2006 |
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| , en , Health-Identity : services mobiles pour les consommateurs de médicaments, market.ch - IBCom, 2009 |
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| , , en , 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, pagina's 22-26, CEUR-WS, 2015 |
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, en , Hierarchical classification using a frequency-based weighting and simple visual features (2008), in: Pattern Recognition Letters, 29:15(2011-2017)
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| en , Hierarchical Multi-atlas Based Segmentation for Anatomical Structures: Evaluation in the VISCERAL Anatomy Benchmarks, in: Medical Computer Vision. Large Data in Medical Imaging, Springer, 2014 |
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| en , Hierarchical multi-structure segmentation guided by anatomical correlations, in: Proceedings of the VISCERAL Challenge at ISBI, Beijing, China, pagina's 32-36, 2014 |
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| , , , , , , , , , , en , 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, pagina's 41-48, 2015 |
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| , , , , en , How clinical information systems can support life science research (2008), in: Swiss Medical Informatics, 64(21-24) |
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, , , , , , en , 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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| , , , , en , How Grids are Perceived in Healthcare and the Public Service Sector, in: Global HealthGrid: e-Science Meets Biomedical Informatics - Proceedings of HealthGrid 2008, pagina's 61-69, 2008 |
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| en , How to Visually Retrieve Images from the St. Andrews Collection Using GIFT., in: Multilingual Information Access for Text, Speech and Images: Result of the fifth CLEF evaluation campaign, pagina's 633-642, Springer, 2005 |
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, , en , How Users Search and What They Search for in the Medical Domain – Understanding Laypeople and Experts Through Query Logs (2016), in: Journal of Information Retrieval
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , 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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, en , Image Classification with a Frequency-based Information Retrieval Schema for ImageCLEF 2006, in: CLEF 2006 Proceedings, pagina's 638-643, 2007
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| , , en , Image Retrieval in Medicine: Motivations, Methods, and Results of the ImageCLEF medical image retrieval task, in: ISHIMR 2007, Sheffield, England, 2007 |
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| , , en , Image Retrieval in Medicine: The imageCLEF 2009 Challenge, in: RSNA 2009, Chicago, IL, USA, 2009 |
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