Schlagworte:
- 2D-based 3D retrieval
- 3D information retrieval
- 3D reconstruction
- 3D texture
- acceptance
- air pollution
- Aneurist
- annotation
- anonymization
- ARC
- Atlas
- Atlas-based segmentation
- Augmented reality
- Bag of visual words
- Bag-of-Colors
- Bayesian methods
- benchmark
- Benchmarking
- big data
- biological organs
- Biological tissue
- biomedical MRI
- CAD
- case-based retrieval
- CFD
- Classification
- clinical data
- clinical data access
- clinical data analysis
- clinical information system
- clinical workflows
- communication protocol
- complex systems
- component-level evaluation
- compound figure separation
- computer tomography
- computer vision
- computer-aided diagnosis
- computerised tomography
- computing infrastructures
- concept vectors
- Content-based image retrieval
- content–based search
- corpus
- crowdsourcing
- CT images
- Cultural heritage
- curriculum learning
- data mining
- datamining imaging indexing ontology radiology
- Deep convolutional neural network
- Deep Learning
- Desktop Grid
- detection
- Diagnostic aid
- DICOM
- Digital hospital
- Discrete wavelet transform
- distributed computing
- Dossier Patient
- efficient access
- eHealth
- Epilepsy
- ethics
- evaluation
- evaluation framework
- experimental evaluation
- eye fundus images
- feature extraction
- feature reuse
- finetuning
- Flickr.
- fracture retrieval
- future internet
- gesture interaction
- GIFT
- glaucoma diagnosis
- gold standard
- google glass
- Grid
- grid computing
- Grid networks
- GridFactory
- ground truth
- Hadoop
- HCI
- health infrastructures
- HealthGrid
- High-resolution lung CT
- Histopathology
- Hospital
- image acquisition
- image analysis
- image browsing
- image categorization
- image classif
- image classification
- Image databases
- Image management
- image processing
- Image registration
- image retrieval
- image retrieval evaluation
- image segmentation
- image storage
- ImageCLEF
- ImageCLEF benchmark
- Informatics
- Information extraction
- information fusion
- information retrieval
- information retrieval evaluation
- information retrieval literature
- information retrieval systems
- Information Systems
- Informatique médicale
- Infrastructures for computation
- Integrating the Healthcare Enterprize
- interfaces
- Interopérabilité.
- Interoperability
- interpretability
- interstitial lung diseases
- inverted file
- key dimension
- language modelling
- large language model
- Lesion detection
- Lesion segmentation
- literature
- log file analysis
- lung
- Lung image
- Lung image analysis
- Lung image retrieval
- lung segmentation
- lung tissue classification
- machine learning
- management
- MapReduce
- MediaEval benchmark
- Medical
- Medical computer vision
- medical image analysis
- Medical image analysis and retrieval
- medical image processing
- Medical image retrieval
- medical image search
- medical imaging
- Medical informatics
- Medical information retrieval
- medical information search
- medical search system
- MeSH
- mobile devices
- mobile information retrieval
- morphometric features
- MRI
- MRML
- multi-atlas based segmentation
- multidimensional image data analysis
- multilingual
- multimedia content analysis
- multimedia library
- multimodal
- Multimodal information retrieval and information fusion
- multimodal retrieval
- Multiple sclerosis
- Natural Language Processing
- Naturalistic studies
- negative relevance feedback
- nosocomial infection
- Open access
- organ segmentation
- Pattern Recognition
- performance evaluation
- pervasive computing
- pollutants dispersion
- precision
- Privacy
- Prototype evaluation
- query drift
- query modification
- query-adaptive fusion
- recall
- Records
- reference database
- region detector
- relevance feedback
- response time
- result diversification
- retrieval
- Riesz
- Riesz transform
- risk of bias
- safe storage
- satisfaction
- scalability
- scientific data
- search
- search context
- Search Interfaces
- search pruning
- Security
- segmentation
- semantic search
- semi-supervised learning
- SIFT
- signal processing
- singular value decompasition
- social photo retrieval
- social web
- Sociology
- speed evaluation
- study design
- support vector machines
- Systematic Review
- systematic reviews
- Systèmes d’Information
- Systems
- target testing
- Taverna
- Telemedicine
- teleradiology
- terminology
- test collection
- test collection creation including signals and images
- text retrieval
- texture analysis
- texture classification
- topic creation
- user interface
- user interfaces
- user modeling
- user modelling
- user testing
- User testing and task analysis
- user-oriented information retrieval
- video retrieval evaluation
- Video-based fieldwork
- Virtual reality
- virtualization
- VISCERAL
- VISCERAL benchmark
- visceral-project
- visual analytics
- visual feature extraction
- visual inforamtion retrieval
- visual information retrieval
- visualization
- wavelet
- wavelets
- Web Applications
- web based interface
- Web services
- Yearbook
Publikationen von Henning Müller sortiert nach erstem Autor
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| , , und , Overview of ImageCLEFtuberculosis 2022 -- CT-based Caverns Detection and Report, in: CLEF working Notes, 2022 |
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| , , und , Overview of ImageCLEFtuberculosis 2022: CT-based cavern detection and report, in: Proceedings of CLEF (Conference and Labs of the Evaluation Forum) 2022 Working Notes, 2022 |
, , , , , , und , Creating a Large-Scale Silver Corpus from Multiple Algorithmic Segmentations, in: MICCAI medical computer vision workshop at MICCAI 2015, Munich, Germany, 2016
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| , , , , , und , Fast Content-based Visual Retrieval of Radiology Cases in Hospital Systems, in: RSNA, Chicago, IL, USA, 2012 |
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| , , , , und , 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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| , , und , VISCERAL: Towards Large Data in Medical Imaging - Challenges and Directions, in: MCBR-CDS MICCAI workshop, Nice, France, 2013 |
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| , , und , VISCERAL: Towards Large Data in Medical Imaging - Challenges and Directions, in: MCBR-CDS MICCAI workshop, Nice, France, 2012 |
| und , Benchmarking multimedia retrieval, 2011 |
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| , , , , und , Augmented medical image management, in: Advanced information and telemedicine technologies for health (AITTH 2005), Minsk, Belarus, 2005 |
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| , , , , und , Augmented Medical Information Management Using Content-Based Image Retrieval, in: Medical Imaging and Telemedicine, Seiten 63-67, 2005 |
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| , , und , DebugIT for Patient Safety - Fight against Emergent Microbial Diseases Using Multimedia Data Mining of Heterogeneous Clinical Data, in: Swiss Conference on Medical Informatics, 2008 |
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| , , und , DebugIT for Patient Safety - Fight Against Emergent Microbial Diseases Using Multimedia Data Mining of Heterogeneous Clinical Data (2008), in: Swiss Medical Informatics, 64(32-35) |
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| , , und , Switzerland as a hub for AI in radiology, in: Swiss congress of radiology 2018, Lausanne, Switzerland, 2018 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Why rankings of biomedical image analysis competitions should be interpreted with care (2018), in: Nature Communications
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions (2018), in: arXiv |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Metrics reloaded: recommendations for image analysis validation (2024), in: Nature Methods |
[DOI] |
| , , und , Metrics reloaded: Pitfalls and recommendations for image analysis validation (2022), in: ArXiv |
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| , , und , The Reality of Content-based Image Retrieval, in: Proceeding of the meeting Suchbilder, Seiten 86-98, 2003 |
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| , , , , , , , , , , , , und , Empowering Digital Pathology Applications through Explainable Knowledge Extraction Tools (2022), in: Journal of Digital Pathology |
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| , , , , , , , , , , , , , , , , , , und , Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations (2022), in: Nature Partner Journal on Digital Medicine |
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| , , , , , , , , , , , und , Multimodal Representations of Biomedical Knowledge from Limited Training Whole Slide Images and Reports using Deep Learning (2024), in: Medical Image Analysis |
[DOI] |
| , , , , , , , , , und , Data-driven color augmentation for H\&E stained images in computational pathology (2023), in: Journal of Pathology Informatics(100183) |
| , , und , A multi-task Multiple Instance Learning algorithm to analyze large whole slide images from the BRIGHT challenge 2022, in: ISBI Challenges 2022, Bangalore India, 2022 |
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| , , , und , Preparing user tests for assessing a medical image retrieval system: A pilot study, in: MedInfo, Copenhagen, Denmark, 2013 |
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| , , , und , 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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| , , , , , , und , A Visual Information Retrieval System for Radiology Reports and the Medical Literature, in: Multimedia modeling conference, Dublin, Ireland, 2014 |
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| , , , , , und , KHRESMOI for radiologists - Visual search in radiology archives and the open-access medical literature (2013), in: Health Management, 13:3(23--24) |
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| , , und , Multi-scale visual words for hierarchical medical image categorization, in: SPIE Medical Imaging 2012: Advanced PACS-based Imaging Informatics and Therapeutic Applications, San Diego, CA, USA, Seiten 83190F-83190F-11, 2012 |
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| , , und , The MedGIFT group at ImageCLEFmed 2011, in: CLEF working notes, Amsterdam, The Netherlands, 2011 |
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, , , , , und , User-oriented evaluation of a medical image retrieval system for radiologists (2015), in: International Journal of Medical Informatics(774-783)
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| , , , , , und , A survey on visual information search behavior and requirements of radiologists, in: Methods of information in Medicine, Seiten 539-548, 2012 |
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| , , , , und , A System for Visual Information Retrieval in Images, Radiology Reports and the Medical Literature, in: RSNA demonstration, Chicago, IL, USA, 2013 |
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| , , , und , Using MapReduce for Large-scale Medical Image Analysis (2015), in: arXiv:1510.06937 |
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| , , , und , Using MapReduce for Large–scale Medical Image Analysis, in: 2nd IEEE Conference on Healthcare Informatics, Imaging and Systems Biology (HISB), La Jolla, California, 2012 |
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| , , und , The Parallel Distributed Image Search Engine (ParaDISE) (2017), in: ArXiv(1701.05596) |
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, und , Evaluating Multimodal Relevance Feedback Techniques for Medical Image Retrieval (2016), in: Journal of Information Retrieval
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| , und , Multi-modal relevance feedback for medical image retrieval, in: SIGIR workshop on Medical Information Retrieval, Gold Coast, Australia, 2014 |
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, , und , Medical image modality classification using discrete Bayesian Networks (2016), in: Computer Vision and Image Understanding
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| , , , , und , VIDIMU. Multimodal video and IMU kinematic dataset on daily life activities using affordable devices (2023), in: Nature Scientific Data |
| , , , , und , Multimodal video and IMU kinematic dataset on daily life activities using affordable devices (2023), in: Scientific Data |
[DOI] |
| , , , , und , A comparative study on wearables and single-camera video for upper-limb out-of-the-lab activity recognition with different deep learning architectures (2023), in: Gait & Posture, 106 |
[DOI] |
| , , , , , , , , , , , und , Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: PMC |
[DOI] |
, , , , und , Proceedings of the International Workshop on Medical Computer Vision (MCV), Springer, LNCS, 2014
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[URL] |
, , , , , , und , Medical Computer Vision: Algorithms for Big Data (MCV2014), Springer, LNCS 8848, 2014
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, , , , , , und , MCV 2015 Workshop, Springer, 2016
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| und , Open Source Software in the Biomedical Domain: Electronic Health Records and other useful applications (2005), in: Swiss Medical Informatics, 55(3-15) |
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| , , , , und , 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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| , , , , und , Predicting non-response to NAC in patients with breast cancer using 3D texture analysis, in: European Congress of Radiology, Vienna, Austria, 2015 |
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und , Summarizing Citation Contexts of Scientific Publications, in: CLEF 2015 proceedings, Toulouse, France, 2015
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| , , , , , , , und , Deep learning uncertainty quantification of cortical lesions in MP2RAGE for missed lesions discovery, European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Conference 2023, 2023 |
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| 1-50 | 51-100 | 101-150 | 151-200 | 201-250 | 251-300 | 301-350 | 351-400 | 401-450 | 451-500 | 501-550 | 551-600 | 601-650 | 651-700 | 701-750 | 751-752 |