Palavras-chave:
- 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
Publicações de Henning Müller ordenado por recente
| , , , , , , , , , and , Imageclef 2026: Multimodal challenges in medicine, science, agritech, and security, in: European Conference on Information Retrieval, Springer, páginas 336--344, 2026 |
| , and , Bag-of-Visual-Words for Spatial Mapping of Lung Adenocarcinoma Growth Patterns (2026), in: arXiv preprint arXiv:2608.05074 |
| , , and , Comparing Baseline and Day-1 Diffusion MRI Using Multimodal Deep Embeddings for Stroke Outcome Prediction, in: 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), IEEE, páginas 1--5, 2026 |
| , and , One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training (2026), in: arXiv preprint arXiv:2608.09403 |
| , , , , , , and , Optimization-enhanced Gaussian mixture modeling for data-driven subphenotyping of septic shock (2026), in: Computer Methods in Biomechanics and Biomedical Engineering(1--14) |
| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline (2026), in: Diagnostic and Interventional Radiology |
| , , , , , , , and , RoBuster—Corpus Annotated With Risk of Bias Text Spans in Randomized Controlled Trials in Physiotherapy and Rehabilitation: Corpus Development and Annotation Study (2026), in: JMIR formative research, 10:1(e55127) |
| , and , An Adaptive Attention-Driven Quadruplet Deep Hashing Method for Retrieving Histopathological Images (2026), in: Journal of Imaging, 12:7(321) |
| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Multi-class segmentation of aortic branches and zones in computed tomography angiography: the aortaseg24 challenge (2026), in: Medical Image Analysis(104188) |
| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Multi-structure segmentation in CBCT volumes: The ToothFairy2 challenge (2026), in: Medical Image Analysis(104095) |
| , , , , , , , , , , and , The consensus-based CINEX guideline for reporting clinical information extraction studies (2026), in: Journal of the American Medical Informatics Association(ocag136) |
| , , , , , , , , and , TransformEEG: Towards Improving Model Generalizability in Deep Learning-based EEG Parkinson's Disease Detection (2025), in: arXiv preprint arXiv:2507.07622 |
| , , , , and , Retrospective Matching Network-Based One-Shot Multi-Object Tracking Method for UAV (2026), in: CONCURRENCY AND COMPUTATION, 38:1 |
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| , , , , and , Biologically constrained Transformers improve stability and interpretability in single-cell transcriptomics, in: Proceedings of Bioinformatics Italian Society 2026, 2026 |
| , , , and , EEG-To-fMRI Cross-Modal Prediction via Hierarchical Temporal Attention Network: Toward Accessible Functional Neuroimaging (2026), in: Concurrency and Computation: Practice and Experience, 38:14(e70860) |
| , , , , , and , An overview of self-supervised deep learning applications to molecular data (2026), in: Briefings in Bioinformatics, 27:4(bbag380) |
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| , , , , , , , , , , and , The TopCoW Challenge—Topology-Aware Circle of Willis Segmentation for CT and MR Angiography (2026), in: NEJM AI, 3:8(AIdbp2500994) |
| , , , , , , , , , , , , , , , , , , and , A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosis (2026), in: NeuroImage: Clinical, 50(104007) |
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| , , , , , , , , , , , , , and , Automatic labels are as effective as manual labels in digital pathology images classification with deep learning (2025), in: Journal of Pathology Informatics, 18(100462) |
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| , , , , , , , and , Improving sEMG signals recognition accuracy using 3D compression and broad learning system (2025), in: SIGNAL, IMAGE AND VIDEO PROCESSING, 19:13 |
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| , , , and , A Ni/CCF@PDMS-based flexible and electromagnetic interference-shielding surface electromyography/electrooculography sensor (2026), in: SENSORS AND ACTUATORS. A, PHYSICAL, 400(117530--117530) |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges (2025), in: Hansen et al. 2025 / Melba Journal - Machine Learning for Biomedical Imaging, Volume 3 |
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| , , , , , , , and , Exploring environmental sustainability of artificial intelligence in radiology: A scoping review (2026), in: European Journal of Radiology, Volume 194 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , and , Automated segmentation of pediatric neuroblastoma on multi-modal MRI: Results of the SPPIN challenge at MICCAI 2023, MDPI Bioengineering, 2025 (2025), in: MDPI Bioengineering, nov. 25 |
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| and , Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge (2025), in: Arxiv |
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| and , KI-gestütztes Videomonitoring aquatischer Ökosysteme - Chancen, Grenzen und Praxisanforderungen (2025), in: Springer Pfofessional, Wasser Wirtschaft, 115(54-61) |
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| , , , , , , , , and , Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges (2025), in: Melba, Volume 3(775-791) |
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| , , and , Exploring environmental sustainability of artificial intelligence in radiology: A scoping review (2025), in: European Journal of Radiology |
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| and , Automated segmentation of pediatric neuroblastoma on multi-modal (2025), in: MDPI Bioengineering |
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| , , , , , , , , and , TransformEEG: Towards improving model generalizability in deep learning-based EEG Parkinson’s disease detection (2025), in: Elsevier |
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| , , , and , BONBID-HIE 2023: Lesion Segmentation Challenge in BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy (2025), in: Publimed |
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| , , , , , , , , , , , and , Multi-Method eXplainability for Similarity Assessment in AI-Denoised PET Imaging, in: 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), páginas 1-4, 2026 |
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| , , and , Automated OCT B-Scan Classification of Macular Scan Volumes with DINOv2 and Multi-Head Attention (2025), in: Investigative Ophthalmology & Visual Science June 2025, Vol.66, 5440., vol. 66 |
| , , , , , , and , Overview of ImageCLEFMedical 2025 GANs Task: Training Data Analysis and Fingerprint Detection (2025), in: CLEF 2025 Working Notes, 9 – 12 September 2025, Madrid, Spain / coeur-ws.org, 4038(paper 169) |
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| , , , , , , , , , , , , , , and , Overview of ImageCLEFmedical 2025 – Medical Concept Detection and Interpretable Caption Generation (2025), in: CEUR-WS.org/Vol-4038 - CLEF 2025 Working Notes, 4038:Paper 170 |
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| and , 3-D Image-to-Image Fusion in Lightsheet Microscopy by Two-Step Adversarial Network: Contribution to the Fusemycells Challenge (2025), in: 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI) |
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| , , , , , , and , LLM-Enhanced Information Mining for Medical Visual Question Answering, Workshop on Large Language Model Using Multi-modal Data for User Modeling, Sydney, Australia, 2025. (2025), in: WWW '25: The ACM Web Conference 2025(2297-2305) |
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| , , , , , and , Diversity-Augmented Diffusion Network With LLM Assistance For Radiology Report Generation (2025), in: WWW '25: Companion Proceedings of the ACM on Web Conference 2025(2288-2296) |
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| and , Automatic Multi-structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures (2025), in: Supervised and Semi-supervised Multi-structure Segmentation and Landmark Detection in Dental Data (MICCAI 2024), 15571(63-71) |
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| , , , , , and , Interpretable AI for medical image analysis (2025), in: The MICCAI Society book Series 2025, Chapter 15(315-346) |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , and , Multimedia Retrieval in Medical, Social Media and Content Recommendation Applications ECIR 2025 (2025), in: Lecture Notes in Computer Science, vol 16089. Springer, Cham., 16089(290-314) |
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| , , , , , , , , , , , , , , and , Challenges on Species Presence Prediction and Identification, and Individual Animal Identification, Springer Lecture Notes in Computer Science, Proceedings of CLEF 2025, Madrid, Spain, 2025. (2025), in: Lecture Notes in Computer Science, vol 15576. Springer, Cham, 15576(373-381) |
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| , , , , , , and , Segmenting the Inferior Alveolar Canal in CBCTs Volumes: The ToothFairy Challenge (2025), in: IEEE Transactions on Medical Imaging, Volume 44, Issue : 4, Arpil 2025(1890-1906) |
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| , , , , , , , , , , , , , , , and , Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction Errors, 2025 |
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| , , , , , , , , , , , and , Impact of CT dose on AI performance: A comparison of radiomics, deep, and foundation models in a multi-centric anthropomorphic phantom study (2026), in: Medical Physics, 53:3(e70374) |
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| , , , , , , , , and , Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation (2025), in: Computers in Biology and Medicine |
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| , and , A comparative study of deep convolutional neural networks for the analysis of retinal damage in optical coherence tomography, in: Imaging Informatics for Healthcare, Research, and Applications, 2024 |
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| , , , , , , , and , A full pipeline to analyze lung histopathology images, in: Digital and Computational Pathology, SPIE Medical Imaging, 2024 |
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