Trefwoorden:
- https://publications.hevs.ch/index.php/keywords/single/197
- (Bio-) Medical Image Registration
- 3D Network
- 3D Segme
- 3D U-Net Author Keywords Segmentation
- 3D-color-grayscale conversion
- Active Learning
- adversarial learning
- algorithms
- Annotation Process
- Annotations
- Aorta segmentation
- AortaSeg24
- Automatic weak labels
- Benchmark testing
- Biodiversity Machine Learning AI Species Individual Identification Prediction Species Distribution Modeling
- Biological signal acquisition
- BLS
- Brain
- Challenge Participants
- Chopped carbon fiber
- citation screening
- Classification
- Clinical decision support
- Common Benchmark
- Computed Tomography Angiography
- computed tomography MeSH Terms Cone-Beam Computed Tomography
- computer vision
- Cone Beam Computed Tomography Deep Learning Image Segmentation ToothFairy
- Cone-beam Computed Tomography Images
- Cone-beam Computed Tomography Volume
- Cortical lesions
- Data Augmentation
- Data Challenges
- Data Challenges · (Bio-) Medical Image Registration
- Deep Learning
- Deep Neural Network
- detection
- Dice Loss
- Dice Similarity Coefficient
- DiffusionModel
- digital pathology
- Domain Dataset
- EEE Keywords Three-dimensional displays
- Electromagnetic interference shielding
- Explainable AI
- explainable AI (XAI)
- Final Ranking
- Flexible sensor
- Focal Loss
- Fuse-MyCells
- Generative Adversarial Networks
- generative models
- Histopathology
- Histopathology image classification
- human-machine interaction
- Humans
- Image Captioning
- image retrieval
- image segmentation
- Image Understanding
- Image-to-Image
- ImageCLEF
- ImageCLEF benchmarking lab
- Imaging
- Inferior Alveolar Canal
- Inferior Alveolar Nerve
- Information extraction
- interpretability
- Intersection Over Union
- Irrigation
- Knowledge Injection
- large language model
- Large Language Models
- Lightsheet Microscopy
- Lung graph model
- machine learning
- Magnetic resonance imaging
- Mandible
- Mandibular Canal
- Medical Experts
- Medical image processing Medical image caption analysis Medical concept prediction Visual question answering Generative Adversarial Networks Synthetic Data Generation Image Segmentation Pictogram communication Multilingual Image Retrieval ImageCLEF
- medical imaging
- medical synthetic data
- Medical Visual Question Answering
- Mental Foramen
- MOT
- Multi-label classification
- multi-task learning
- Multimodal Learning
- Multiple sclerosis
- Multiview Fusion
- Natural Language Processing
- Neural Network
- Noisy labels
- Panoramic Radiographs
- Private Dataset
- Proposals Index Terms Inferior Alveolar
- Public Datasets
- Pulmonary embolism
- Pulmonary hypertension
- Radiology
- Radiology Report Generation
- retrospective matching network
- Scanning electron microscopy
- segmentation
- SEMG
- semi-supervised learning
- Sparse Labeling
- Statistical Shape Model
- Surgery
- Systematic Review
- systematic reviews
- Teeth
- texture analysis
- Three-Dimensional
- tooth
- training
- Training Data
- Training Set
- Trustworthy AI
- UAV
- whole slide imaging
- wrong labels
- X-ray imaging
Publicaties van Henning Müller gesorteerd op nieuwheid
| , , , , , , , , en , Gaze, behavioral, and clinical data for phantom limbs after hand amputation from 15 amputees and 29 controls (2020), in: Scientific Data, 7:1(1--14) |
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| , , , , en , Benchmarking Image Retrieval Diversification Techniques for Social Media (2020), in: IEEE Transactions on Multimedia |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , Overview of the ImageCLEF 2020: Multimedia Retrieval in Medical Lifelogging, Nature and Internet Applications, in: CLEF Proceedings, 2020 |
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| , , , en , Overview of the VQA-Med Task at ImageCLEF 2020: Visual Question Answering and Generation in the Medical Domain, in: CLEF workingnotes 2020, Thessaloniki Greece,, 2020 |
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| , , , , , , , , , en , BIAS: Transparent reporting of biomedical image analysis challenges (2020), in: Medical Image Analysis |
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| , , , , , , , , , , , , , , , , en , Overview of LifeCLEF 2020: a System-oriented Evaluation of Automated Species Identification and Species Distribution Prediction, Thessaloniki, Greece, Springer LNCS, 2020 |
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| , , en , Guiding CNNs towards Relevant Concepts by Multi-task and Adversarial Learning, arxiv, 2020 |
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| , , , en , 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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, , , , , en , A lung graph model for the radiological assessment of chronic thromboembolic pulmonary hypertension in CT (2020), in: Computers in Biology and Medicine(103962)
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| , en , Concept attribution: Explaining CNN decisions to physicians (2020), in: Computers in Biology and Medicine |
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| , , en , Consistency of Scale Covariance in Internal Representations of CNNs, in: Irish Machine Vision and Image Processing Conference, 2020 |
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| , , , , , , en , Standardised convolutional filtering for radiomics, 2020 |
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| , , , , en , A systematic comparison of deep learning strategies for weakly supervised Gleason grading,, in: SPIE Medical Imaging, Houstonm, TX, USA, 2020 |
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, en , A large calibrated database of hand movements and grasp kinematics (2020), in: Scientific Data
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| , , , , , , en , An Exploration of Uncertainty Information for Segmentation Quality Assessment, in: SPIE Medical Imaging 2020: Image Processing, Houston, TX, USA, pagina's 381-390, SPIE, 2020 |
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| , , , , en , Information Fusion for Medical Data: early, late and deep fusion methods for multimodal data (2020), in: Journal of Biomedical and Health informatics |
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| , , , , en , Using Publicly Available Medical Images from the Open Access Literature and Social Networks for Model Training and Knowledge Extraction, in: Multimedia Modeling (MMM 2020), Seoul, Korea, 2020 |
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| , , , en , Automating quality control for standardized structured radiology reports using text analysis, in: ECR 2020, Vienna, Austria, 2020 |
| , en , ImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications, in: ECIR 2020, Lisbon Portugal, Springer LNCS, 2020, 2020 |
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| , , en , Machine Learning Assisted Citation Screening for Systematic Reviews, in: Medical Informatics Europe 2020, Geneva, Switzerland, 2020 |
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| , , , en , Exploiting the PubMed Central repository to mine out a large multimodal dataset of rare cancer studies, in: SPIE Medical Imaging, Houston, TX, USA, 2020 |
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| , , en , Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020 |
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| , , , , , , , , , , , , , , en , LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges, in: ECIR 2020, Lisbon, Portugal, Springer LNCS, 2020 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)
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| , en , Interpreting intentionally flawed models with linear probes, in: ICCV workshop on statistical deep learning in computer vision, Seoul, Korea, 2019 |
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| en , Lung Graph-Model Classification with SVM and CNN for Tuberculosis Severity Assessment and Automatic CT Report Generation, in: CLEF working notes 2019, Lugano Switzerland, 2019 |
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| , , , , , , en , Identification and retrieval of prostate cancer cases using a content-based search tool (2019), in: Pathology Informatics |
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| , , , en , Deep learning based retrieval system for gigapixel histopathology cases and open access literature (2019), in: Pathology Informatics |
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, , , , , en , Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography (2019), in: Computer Methods and Programs in Biomedicine
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| , , , , en , Kinematic synergies of hand grasps, in: ESB 2019, Vienna, Austria, 2019 |
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| , , en , Kinematic synergies of hand grasps: a comprehensive study on a large publicly available dataset (2019), in: Journal of Neuroengineering and rehabilitation |
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| , , , en , Analyzing the trade-off between training session time and performance in myoelectric hand gesture recognition during upper limb movement, in: 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), Toronto, Canada, 2019 |
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, , en , CLEF 2019 Working Notes, in: CEUR Workshop Proceedings (CEUR- WS.org), 2019
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| en , Combining object recognition, gaze tracking and electromyography to guide prosthetic hands: experiences from two reserch projects (2019), in: Jedlik Laboratory reports, VII:2 |
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| , , , , , , , , en , Effects of hand amputation surgery procedures on phantom limb sensation, in: FESSH, Berlin, Germany, 2019 |
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| , , , , , , , , en , Effects of hand amputation surgery procedures on sEMG activity to control robotic hand prostheses, in: FESSH, Berlin, Germany, 2019 |
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| , , , en , An Augmented Reality Environment to Provide Visual Feedback to Amputees during sEMG Data Acquisitions, in: TAROS (Towards Autonomous Robotic Systems), London, United Kingdom, 2019 |
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| , , , , , , , en , Experimental IR Meets Multilinguality, Multimodality, and Interaction, Springer, LNCS, 2019 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , ImageCLEF 2019: Multimedia Retrieval in Lifelogging, Medical, Nature and Security Applications, in: CLEF conference Proceedings, Lugano, Switzerland, Springer LNCS, 2019 |
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| , , en , A Graph Model of the Lungs with Morphology-based Structure for Tuberculosis Type Classification, in: The 26th International Conference on Information Processing in Medical Imaging (IPMI), 2019 |
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| , , , , , , , , en , Improved interpretability for computer-aided severity assessment of retinopathy of prematurity, in: SPIE Medical Imaging, San Diego, CA, USA, 2019 |
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| , , , , , , , , , , , , , , , , , , , , , , en , Heterogeneous exascale computing, in: INES 2018 conference, Springer, 2019 |
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| en , EaaS – Evaluation-as-a-Service in scientific challenges, Springer, 2019 |
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| , en , Experiences from the ImageCLEF Medical Retrieval and Annotation Tasks, Springer, 2019 |
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, , , , en , A Quantitative Taxonomy of Human Hand Grasps, (2019), in: Journal of NeuroEngineering and Rehabilitation,, 16:28
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| , , , , , , , , , , , , , , , , , , , , , , , , en , ImageCLEF 2019: Multimedia Retrieval in Medical Nature, Security and Lifelogging Applications, in: ECIR 2019, Cologne, Germany, 2019 |
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| , , , , , , , en , Biodiversity information retrieval through content-based identification: a long-term evaluation, Springer, 2019 |
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| , , , , , , , en , LifeCLEF 2019: Biodiversity Identification and Prediction Challenges, in: ECIR 2019, Cologne, Germany, 2019 |
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| , en , 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, pagina's 109-116, SPIE, 2019 |
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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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