Schlagworte:
- 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
Publikationen von Henning Müller sortiert nach Aktualität
| , , , , , und , Automating Quality Control for Structured Standardized Radiology Reports Using Text Analysis., in: Medical Informatics Europe 2020, Geneva, Seiten 58--62, IOS Press, 2020 |
[DOI] [URL] |
| , , , , und , Questioning Domain Adaptation in Myoelectric Hand Prostheses Control: An Inter-and Intra-Subject Study (2021), in: Sensors, 21:22(7500) |
| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Common limitations of performance metrics in biomedical image analysis, in: MIDLconference, 2021 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , und , ImageCLEF 2021: Multimedia Retrieval in Medical, Nature, Internet and Social Media, in: CLEF proceedings, Springer, 2021 |
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| , , , , , , , , , , , , , , , , , und , Overview of LifeCLEF 2021: an Evaluation of Machine-Learning based Species Identification and Species Distribution Prediction, in: CLEF proceedings, Springer, 2021 |
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| , , , , und , Overview of the ImageCLEFmed 2021 Concept & Caption Prediction Task, in: CLEF working notes, 2021 |
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| , , , und , Overview of the VQA-Med Task at ImageCLEF 2021: Visual Question Answering and Generation in the Medical Domain, in: CLEF working notes, 2021 |
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| , , , und , Overview of ImageCLEFtuberculosis 2021 - CT-based Tuberculosis Type Classification, in: CLEF working notes, 2021 |
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| , , , , , , , und , Multi-Scale Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations, in: COMPAY workshop at MICCAI, 2021 |
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| , , und , Classification of noisy free-text prostate cancer pathology reports using natural language processing, in: Workshop AIDP at ICPR, 2021 |
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| , , , und , An End-to-End 3D ConvLSTM-based Framework for Early Diagnosis of Alzheimer's Disease from Full-Resolution Whole-Brain sMRI Scans, in: Computer-Based Medical Systems, 2021 |
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| , , , und , H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression, in: ICCV 2021 workshop on Computational Challenges in Digital Pathology, 2021 |
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| , , , und , End-to-end Fine-grained Neural Entity Recognition of Patients, Interventions, and Outcomes, in: CLEF proceedings, 2021 |
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| , , , , , , , , und , CLEF proceedings, Springer, LNCS, 2021 |
| , , , , , , und , Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images (2021), in: Frontiers in Computer Science |
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| , , , , , und , An AI-based algorithm for the automatic classification of thoracic radiographs in cats (2021), in: Frontiers in Veterinary science |
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| , , und , Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: an experiment on histopathology image classification (2021), in: Medical Image Analysis |
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| , , , , , , , und , Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods (2021), in: Journal of Personalized Medicine, 11:9 |
[URL] |
, , , , , und , Radiomics Analysis Using The Image Biomarker Standardization Initiative (IBSI) Benchmarks And Guidelines, in: Radiological Society of North America (RSNA) 2021 Annual Meeting, 2021
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| , , , , und , Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability, in: MICCAI 2021, Springer, 2021 |
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| , , , , , , , , , und , PROCESS Data Infrastructure and Data Service (2020), in: Computing and Informatics |
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| und , InvNet: A Deep Learning Approach to Invert Complex Deformation Fields, in: ISBI, Nice, France, 2021 |
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| , , und , 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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und , DeepHistReg: Unsupervised Deep Learning Registration Framework for Differently Stained Histology Samples (2021), in: Computer Methods and Programs in Biomedicine
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| , , und , Combining weak and strong supervised learning improves strong supervision in Gleason pattern classification (2021), in: BMC Medical Imaging |
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, , , , , , , , und , The discriminative power and stability of radiomics features with CT variations: Task-based analysis in an anthropomorphic 3D-printed CT phantom (2021), in: Investigative Radiology, 56:12(820-825)
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| , , , und , On the Scale Invariance in State of the Art CNNs Trained on ImageNet (2021), in: Special Issue "Interpretable and Annotation-Efficient Learning for Medical Image Computing" in Machine Learning and Knowledge Extraction:3(374–391) |
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| , , , , , , , , und , 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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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , 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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| , , , , , , , , , , und , LifeCLEF 2021 teaser: Biodiversity Identification and Prediction Challenges, in: European Conference on Information Retrieval, 2021 |
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| , , , , , , , , und , 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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| , , und , Evaluation and Comparison of CNN Visual Explanations for Histopathology, in: XAI-AAAI-21, 2021 |
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| , und , Availability of sEMG controlled prosthetic arm components, Information Systems Institute, HES-SO Valais; EPFL, 2020 |
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, , , , und , The Importance of Feature Aggregation in Radiomics: A Head and Neck Cancer Study (2020), in: Nature Scientific Reports, 10:19679
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| , , , , , , , , , und , Reference Exascale Architecture - Extended Version (2020), in: Computer And Informatics |
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| , , , , und , Breast Histopathology with High-Performance Computing and Deep Learning (2020), in: Computer and Informatics |
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| , , , , und , Overview of ImageCLEFtuberculosis 2020: Automatic CT-based report generation, in: CLEF working notes, CEUR, 2020 |
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| , , und , Overview of the ImageCLEFmed 2020 Concept Prediction Task: Medical Image Understanding, in: CLEF working notes, CEUR, 2020 |
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| , , , , und , Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020 |
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| und , 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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| , , , , , , , , , , , , und , Gaze, visual,myoelectric data of grasps for intelligent prosthetics (2020), in: Nature Scientific Data |
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| , , und , Variability of Muscle Synergies in Hand Grasps: Analysis of Intra-and Inter-Session Data (2020), in: Sensors, 20:15(4297) |
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| , , , , und , Prospects and Challenges of Radiomics by Using Nononcologic Routine Chest CT, in: Radiology: Cardiothoracic Imaging, 2020 |
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| , , und , 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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| , , und , Eye-hand coordination to improve grasp-type recognition in hand prostheses, in: Cybathlon Symposium, Zürich, Switzerland, 2020 |
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| und , Learning-Based Affine Registration of Histological Images, in: International Workshop on Biomedical Image Registration, Springer, Seiten 12--22, 2020 |
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| , , , , und , 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, Seiten 1758--1761, 2020 |
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| , , , und , 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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| , , , und , Multimodal Latent Semantic Alignment for Automated Prostate Tissue Classification and Retrieval, in: MICCAI, Lima, Peru, 2020 |
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| , Medical Image Retrieval: Applications and Resources, in: International Conference on Multimedia Retrieval, 2020 |
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