Institute of Informatics (II)
Topic: MedGIFT
Publications for topic "MedGIFT" sorted by journal and type
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Publications of type Incollection
2010
| and , Fusion Techniques for Combining Textual and Visual Information Retrieval, in: ImageCLEF, pages 95-114, Springer Berlin Heidelberg, 2010 |
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| and , Seven Years of ImageCLEF, in: ImageCLEF Book, pages 3-18, Springer, 2010 |
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| , and , The ImageCLEF Medical Image Retrieval Task, in: ImageCLEF – Experimental evaluation of visual information retrieval, pages 221-238, Springer, 2010 |
Publications of type Inproceedings
2026
| , , , , , , and , AI-based response assessment and prediction in longitudinal imaging for brain metastases treated with stereotactic radiosurgery, in: Learning with Longitudinal Medical Images and Data at MICCAI 2025, pages 102-112, Springer Nature Switzerland, 2026 |
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| , , , , , and , Dynamic Modeling of Brain Metastasis Response with Multitask Temporal Learning, in: Medical Image AI in Radiation Therapy (MIART) at MICCAI 2026, 2026 |
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| , , , , , , , and , Multi-depth Rubidium PET Graph Neural Network for Major Adverse Cardiac Event Prediction, in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2026, 2026 |
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2025
| , , , , , , , , , , and , Deep-PRL: a deep learning network for the identification of paramagnetic rim lesions in multiple sclerosis, in: ISMRM 2025, 2025 |
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| , , , , , , and , Exploiting XAI maps to improve MS lesion segmentation and detection in MRI, in: Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI, 2025 |
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2024
| , , , , and , A Bispectral 3D UNet for Rotation Robustness in Medical Segmentation, in: The First Workshop on Topology- and Graph-Informed Imaging Informatics at MICCAI, pages 43-54, Springer Nature Switzerland, 2024 |
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| , , , , , , , and , Instance-level explanations in multiple sclerosis lesion segmentation: a novel localized saliency map, in: ISMRM 2024, 2024 |
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2023
| , , , , , , , and , FLAIR vs MPRAGE contribution to white matter lesion automatic segmentation in MS using localized saliency maps, in: Bern Interpretable AI Symposium (BIAS), 2023 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Identification of paramagnetic rim lesions using conventional MRI - a deep learning approach, in: 39th Congress Of The European Committee For Treatment And Research In Multiple Sclerosis (ECTRIMS), 2023 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT, pages 1-30, Springer, Cham, 2023 |
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| , , , , , , and , Rethinking the Role of AI with Physicians in Oncology: Revealing Perspectives from Clinical and Research Workflows, in: ACM CHI 2023, 2023 |
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2022
| , , , , , , , and , Comparison of MR preprocessing strategies and sequences for radiomics-based MGMT prediction, in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (MICCAI/BrainLes 2021), Cham, pages 367–380, Springer International Publishing, 2022 |
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| , , , , , , , and , HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022 |
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| , , , and , Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectral U-Net, in: Medical Imaging with Deep Learning, 2022 |
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| , , , , , , , , , and , Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images, in: Head and Neck Tumor Segmentation and Outcome Prediction, pages 1-37, 2022 |
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| , , , , , , , and , QuantImage v2: A Clinician-in-the-loop Cloud Platform for Radiomics Research, in: European Society of Radiology, 2022 |
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| , , , , and , Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT, in: 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pages 4731-4735, 2022 |
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| , , , , , and , The Image Biomarker Standardisation Initiative (IBSI) On Reproducible Convolutional Radiomics, in: European Society of Radiology, 2022 |
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2021
| , , , , , , , , and , 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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| , , , , , and , Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, pages 59-68, Springer LNCS, 2021 |
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| , , , , , and , Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer, in: 4th Workshop on PRedictive Intelligence in MEdicine, pages 147-156, Springer LNCS, 2021 |
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| , , , and , QuantImage v2: an Open-Source and Web-Based Integrated Platform for Clinical Radiomics Research, in: Joint scientific session SSRMP/SGR-SSR, 2021 |
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| , , , , , , , , 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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2020
| , , , , , , , and , Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans, in: Medical Imaging with Deep Learning, Montréal, Canada, 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 , 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 , 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 , Oropharynx Detection in PET-CT for Tumor Segmentation, in: Irish Machine Vision and Image Processing Conference, 2020, 2020 |
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2019
| , , and , A lung graph model for the classification of interstitial lung disease on CT images, in: SPIE Medical Imaging 2019: Computer-Aided Diagnosis, International Society for Optics and Photonics, pages 869-876, SPIE, 2019 |
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, , , and , Exploring local rotation invariance in 3D CNNs with steerable filters, in: Medical Imaging with Deep Learning, pages 15-26, Proceedings of Machine Learning Research, 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 , Radial B-Splines for Optimal Detection in Images, in: ISBI Special Session on Spline Models in Biomedical Imaging, 2019 |
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| , , , and , Solid Spherical Energy (SSE) CNNs for Efficient 3D Medical Image Analysis, in: Irish Machine Vision and Image Processing Conference, pages 37-44, 2019 |
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2018
| , and , Distributed container-based evaluation platform for private/large datasets, in: ISPDC 2018, Geneva, Switzerland, 2018 |
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| , , , and , Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features, in: Machine Learning in Medical Imaging (MLMI), pages 107--115, Springer International Publishing, 2018 |
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2017
| , , , , , , and , Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score, in: SPIE Medical Imaging, pages 101400O-101400O-9, 2017 |
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2016
| , and , A Demo of Multimodal Medical Retrieval, in: Workshop on Content-based Multimedia Indexing (CBMI), Bucharest, Romania, 2016 |
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| , , , , , and , A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT images, in: MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, pages 58-68, 2016 |
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| , , and , Clinical, anatomical and external factors to improve dexterous robotic hand prostheses, in: XXI Congress of the Federation of European Societies for Surgery of the Hand (FESSH), Santander, Spain, 2016 |
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| , , , , , , , , , , , , , , , , , , and , Computational Fluid Dynamics as a tool to predict the air pollution dispersion in a neighbourhood – A research project to improve the quality of life in cities, in: Air pollution, Crete, Greece, 2016 |
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, , , , , , and , 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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| , , , , and , Div150Multi: A Social Image Retrieval Result Diversification Dataset with Multi-topic Queries, in: Multimedia Systems, Klagenfurt, Austria, 2016 |
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| , , and , Electromyography for Hand Prosthetics Demo, in: XXVIII Conférence francophone sur l'Interaction Homme-Machine, Fribourg, Suisse, 2016 |
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| , , , and , From NinaPro to MeganePro towards the natural control of myoelectric prosthetic hands, in: Cybathlon Symposium, Zurich, Switzerland, 2016 |
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| , , , , , , , , , , , , , , , and , General Overview of ImageCLEF at the CLEF 2016 Labs, in: CLEF Proceedings, Springer, 2016 |
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| , , , , and , GPU-Accelerated Texture Analysis Using Steerable Riesz Wavelets, in: 24th IEEE Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Heraklion Crete, Greece, pages 431--434, 2016 |
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| , , , , and , 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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| 1-50 | 51-100 | 101-150 | 151-200 | 201-250 | 251-300 | 301-350 | 351-400 | 401-450 | 451-500 | 501-550 | 551-600 | 601-607 |