Keywords:
- 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
Publications of Henning Müller sorted by journal and type
Publications of type Inproceedings
2021
| , , , , , , , , and , Revealing most suitable CT radiomics features for retrospective studies with heterogeneous datasets, in: European Congress of Radiology (ECR) 2021, ONLINE edition, 2021 |
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| , , and , Semi-supervised learning with a teacher-student paradigm for histopathology classification: a resource to face data heterogeneity and lack of local annotations, in: Workshop Artificial Intelligence for Digital Pathology, ICPR, Milano, Italy, 2021 |
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| , , , , and , Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability, in: MICCAI 2021, Springer, 2021 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , The 2021 ImageCLEF Benchmark: Multimedia Retrieval in Medical, Nature, Internet and Social Media Applications, in: European Conference on Information Retrieval, Springer, 2021 |
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2020
| , , , , and , A systematic comparison of deep learning strategies for weakly supervised Gleason grading,, in: SPIE Medical Imaging, Houstonm, TX, USA, 2020 |
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| , , , , , , and , An Exploration of Uncertainty Information for Segmentation Quality Assessment, in: SPIE Medical Imaging 2020: Image Processing, Houston, TX, USA, pages 381-390, SPIE, 2020 |
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| , , , and , Automating quality control for standardized structured radiology reports using text analysis, in: ECR 2020, Vienna, Austria, 2020 |
| , , , , , and , Automating Quality Control for Structured Standardized Radiology Reports Using Text Analysis., in: Medical Informatics Europe 2020, Geneva, pages 58--62, IOS Press, 2020 |
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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 , Effect of movement type on the classification of electromyography data for the control of dexterous prosthetic hands, in: Biorob, International Conference on Biomedical Robotics & Biomechatronics, New York City, NY, USA, 2020 |
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| , , , and , 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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| , , and , Eye-hand coordination to improve grasp-type recognition in hand prostheses, in: Cybathlon Symposium, Zürich, Switzerland, 2020 |
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| , , and , Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020 |
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| , and , ImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications, in: ECIR 2020, Lisbon Portugal, Springer LNCS, 2020, 2020 |
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| , , , and , 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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| and , Learning-Based Affine Registration of Histological Images, in: International Workshop on Biomedical Image Registration, Springer, pages 12--22, 2020 |
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| , , , , , , , , , , , , , , and , LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges, in: ECIR 2020, Lisbon, Portugal, Springer LNCS, 2020 |
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| , , and , Machine Learning Assisted Citation Screening for Systematic Reviews, in: Medical Informatics Europe 2020, Geneva, Switzerland, 2020 |
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| , Medical Image Retrieval: Applications and Resources, in: International Conference on Multimedia Retrieval, 2020 |
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| , , , and , Multimodal Latent Semantic Alignment for Automated Prostate Tissue Classification and Retrieval, in: MICCAI, Lima, Peru, 2020 |
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| , , , , and , Overview of ImageCLEFtuberculosis 2020: Automatic CT-based report generation, in: CLEF working notes, CEUR, 2020 |
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| , , , , , , , , , , , , , , , , and , 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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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Overview of the ImageCLEF 2020: Multimedia Retrieval in Medical Lifelogging, Nature and Internet Applications, in: CLEF Proceedings, 2020 |
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| , , and , Overview of the ImageCLEFmed 2020 Concept Prediction Task: Medical Image Understanding, in: CLEF working notes, CEUR, 2020 |
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| , , , and , 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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| , , , , and , Prospects and Challenges of Radiomics by Using Nononcologic Routine Chest CT, in: Radiology: Cardiothoracic Imaging, 2020 |
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| , , and , Semi-Weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks, in: MICCAI workshop Labels, Lima, Peru, 2020 |
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| , , , , and , Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020 |
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| , , , , and , Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading, in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC), IEEE, pages 1758--1761, 2020 |
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| and , Unsupervised Learning-based non-rigid registration of high resolution histology images, in: MICCAI workshop on Machine Learning in Medical Imaging, Springer, 2020 |
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| , , , , and , 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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2019
| , , and , 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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| , , , and , 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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| , , , and , 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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, , and , CLEF 2019 Working Notes, in: CEUR Workshop Proceedings (CEUR- WS.org), 2019
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| , , , , , , , , and , Effects of hand amputation surgery procedures on phantom limb sensation, in: FESSH, Berlin, Germany, 2019 |
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| , , , , , , , , and , Effects of hand amputation surgery procedures on sEMG activity to control robotic hand prostheses, in: FESSH, Berlin, Germany, 2019 |
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| , , , , , , , , , , , , , , , , , , , , , , and , Heterogeneous exascale computing, in: INES 2018 conference, Springer, 2019 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , ImageCLEF 2019: Multimedia Retrieval in Lifelogging, Medical, Nature and Security Applications, in: CLEF conference Proceedings, Lugano, Switzerland, Springer LNCS, 2019 |
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| , , , , , , , , , , , , , , , , , , , , , , , , and , ImageCLEF 2019: Multimedia Retrieval in Medical Nature, Security and Lifelogging Applications, in: ECIR 2019, Cologne, Germany, 2019 |
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| , , , , , , , , and , Improved interpretability for computer-aided severity assessment of retinopathy of prematurity, in: SPIE Medical Imaging, San Diego, CA, USA, 2019 |
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| , and , Interpreting intentionally flawed models with linear probes, in: ICCV workshop on statistical deep learning in computer vision, Seoul, Korea, 2019 |
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| , , , , and , Kinematic synergies of hand grasps, in: ESB 2019, Vienna, Austria, 2019 |
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| , and , 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, pages 109-116, SPIE, 2019 |
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| , , , , , , , and , LifeCLEF 2019: Biodiversity Identification and Prediction Challenges, in: ECIR 2019, Cologne, Germany, 2019 |
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| and , 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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Publications of type Misc
2025
| , , , , , , , , , , , , , , , and , Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction Errors, 2025 |
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2020
| , , and , Guiding CNNs towards Relevant Concepts by Multi-task and Adversarial Learning, arxiv, 2020 |
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| , , , , , , and , Standardised convolutional filtering for radiomics, 2020 |
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Publications of type Techreport
| , and , Availability of sEMG controlled prosthetic arm components, Information Systems Institute, HES-SO Valais; EPFL, 2020 |
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