Schlagworte:
- https://publications.hevs.ch/index.php/keywords/single/197
- 3D information retrieval
- 3D texture
- AI
- ARC
- artificial intelligence
- Atlas
- Automatic segmentation
- Benchmarking
- big data
- Biological tissue
- CAD
- case-based retrieval
- Challenge
- Classification
- clinical data
- clinical data analysis
- clinical workflows
- Computer Vision and Pattern Recognition (cs.CV)
- computer-aided diagnosis
- computerised tomography
- computing infrastructures
- Content-based image retrieval
- conversation analysis
- cs.CV
- data mining
- Desktop Grid
- Discrete wavelet transform
- eHealth
- Epilepsy
- ethnomethodology
- evaluation
- exoticism
- feature extraction
- FOS: Computer and information sciences
- fracture retrieval
- Grid
- Hadoop
- head and neck cancer
- Healthcare
- HealthGrid
- High-resolution lung CT
- Hospital
- Human-Centered Computing
- image acquisition
- image analysis
- image classif
- image classification
- Image databases
- image processing
- image retrieval
- image storage
- ImageCLEF
- information fusion
- information retrieval
- information retrieval evaluation
- information retrieval literature
- Information Systems
- Infrastructures for computation
- interstitial lung diseases
- Lesion detection
- Lesion segmentation
- lung
- Lung image
- Lung image analysis
- Lung image retrieval
- lung segmentation
- lung tissue classification
- machine learning
- Machine Learning (cs.LG)
- MapReduce
- medical image analysis
- Medical image analysis and retrieval
- medical image processing
- Medical image retrieval
- medical imaging
- Medical informatics
- Medical information retrieval
- mentalism
- mobile devices
- mobile information retrieval
- MRI
- multi-atlas based segmentation
- multidimensional image data analysis
- multimedia library
- Multimodal information retrieval and information fusion
- Multiple sclerosis
- nosocomial infection
- oncology
- organ segmentation
- Oropharynx
- radiomics
- retrieval
- Riesz
- Riesz transform
- scalability
- Security
- signal processing
- social interaction
- support vector machines
- Systematic Review
- Taverna
- technologism
- test collection
- test collection creation including signals and images
- texture analysis
- texture classification
- user interface
- user interfaces
- User testing and task analysis
- virtualization
- visceral-project
- visual feature extraction
- visual inforamtion retrieval
- visual information retrieval
- wavelet
- wavelets
- Yearbook
Publikationen von Adrien Depeursinge sortiert nach erstem Autor
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| und , Quality Assessment for Interoperable Quantitative CT imaging (QA4IQI) - Open access to standardized quantitative imaging, HES-SO Valais-Wallis, 2022 |
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| , , , , , , , , und , Locoregional radiogenomic models to capture gene expression heterogeneity in glioblastoma (2018), in: biorXiv |
[DOI] [URL] |
, , , , und , Near–Affine–Invariant Texture Learning for Lung Tissue Analysis Using Isotropic Wavelet Frames (2012), in: IEEE Transactions on Information Technology in BioMedicine, 16:4(665-675)
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[DOI] |
| , , und , Lung Tissue Analysis Using Isotropic Polyharmonic B-Spline Wavelets, in: MICCAI 2008 Workshop on Pulmonary Image Analysis, Seiten 125-134, 2008 |
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, , , , , und , Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows (2012), in: International Journal of Computer Assisted Radiology and Surgery, 7:1(97-110)
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[DOI] [URL] |
| , , , , , und , Content-based retrieval and analysis of HRCT images from patients with interstitial lung diseases: a comprehesive diagnostic aid framework, in: Computer Assited Radiology and Surgery (CARS) 2010, Geneva, Switzerland, 2010 |
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, , , , und , Building a Reference Multimedia Database for Interstitial Lung Diseases (2012), in: Computerized Medical Imaging and Graphics, 36:3(227-238)
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[DOI] |
| , , , , und , Content-based retrieval and analysis of HRCT images from patients with interstitial lung diseases, in: HUG Research Day 2009, 2009 |
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| , , , , und , 3D Case–Based Retrieval for Interstitial Lung Diseases, in: MCBR-CDS 2009: Medical Content-based Retrieval for Clinical Decision Support, London, UK, Seiten 39--48, Springer, 2010 |
[DOI] |
, , und , Predicting Adenocarcinoma Recurrence Using Computational Texture Models of Nodule Components in Lung CT (2015), in: Medical Physics, 42:4(2054-2063)
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[DOI] [URL] |
| , , und , 3D Lung Image Retrieval Using Localized Features, in: Medical Imaging 2011: Computer-Aided Diagnosis, Orlando, FL, USA, Seiten 79632E, SPIE, 2011 |
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| , , , , , und , QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, Seiten 349-377, Elsevier, 2017 |
[URL] |
| , , , , und , Pulmonary Embolism Detection using Localized Vessel-Based Features in Dual Energy CT, in: SPIE Medical Imaging, Seiten 941407-941407-10, SPIE, 2015 |
[DOI] [URL] |
| , , und , Efficient and fully automatic segmentation of the lungs in CT volumes, in: Proceedings of the VISCERAL Anatomy Grand Challenge at the 2015 IEEE ISBI, New York, USA, Seiten 31-35, CEUR-WS, 2015 |
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| , , , , , und , 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, Seiten 58-68, 2016 |
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, , , und , 3-D Solid Texture Classification Using Locally-Oriented Wavelet Transforms (2017), in: IEEE Transactions on Image Processing, 26:4(1899-1910)
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[DOI] |
| , und , QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT, Demonstration at SPIE MI 2017, 2017 |
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| , , und , Mobile Medical Image Retrieval, in: Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications, Orlando, FL, USA, Seiten 79670G, SPIE, 2011 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Why is the winner the best?, in: CVPR, 2023 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Biomedical image analysis competitions: The state of current participation practice (2022), in: arXiv |
[DOI] [URL] |
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| , , , , und , Radial B-Splines for Optimal Detection in Images, in: ISBI Special Session on Spline Models in Biomedical Imaging, 2019 |
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, , , , und , Principled Design and Implementation of Steerable Detectors (2021), in: IEEE Transactions on Image Processing, 30(4465-4478)
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[DOI] |
| , , , , , , , , , und , Lung lesion detectability on images obtained from decimated and CNN-based denoised [18F]-FDG PET/CT scan: An observer-based study for lung-cancer screening (2025), in: European Journal of Nuclear Medicine and Molecular Imaging |
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| , , , , , , , , , und , Lung lesion detectability on decimated and CNN-based denoised 18F-FDG PET/CT, in: Swiss Congress of Radiology, 2024 |
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| , , , , , und , Reproducibility of lung cancer radiomic features extracted from data-driven respiratory gating and free-breathing flow imaging in 18F-FDG PET/CT, in: 2022 Annual Meeting of the Society of Nuclear Medicine and Molecular Imaging (SNMMI), 2022 |
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, , , , , und , Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT (2022), in: European Journal of Hybrid Imaging, 6:1(33)
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, , , , , , , , und , Assessing radiomics feature stability with simulated CT acquisitions (2022), in: Scientific Reports, 12:1(4732)
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| , , und , Three dimensional multi–scale visual words for texture–based cerebellum segmentation, in: Medical Imaging 2012: Image Processing, San Diego, CA, USA, Seiten 83142Z, SPIE, 2012 |
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| , und , Using Multiscale Visual Words for Lung Texture Classification and Retrieval, in: Medical Content-based Retrieval for Clinical Decision Support, Toronto, Canada, Seiten 69-79, Lecture Notes in Computer Sciences (LNCS), 2012 |
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| , , , , und , Benefits of texture analysis of dual energy CT for computer-aided pulmonary embolism detection, in: The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Osaka, Japan, Seiten 3973-3976, 2013 |
[DOI] |
| , und , Visual Grammar: a language modelling approach for building efficient and meaningful bags of visual words (2017), in: ArXiv(1835004) |
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, und , Retrieval of high-dimensional visual data: current state, trends and challenges ahead (2014), in: Multimedia Tools and Applications, 69:2(539-567)
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[DOI] [URL] |
| , und , Region-based volumetric medical image retrieval, in: SPIE Medical Imaging: Advanced PACS-based Imaging Informatics and Therapeutic Applications, Orlando, FL, USA, Seiten 867406-867406-10, SPIE, 2013 |
[DOI] [URL] |
| , , , , und , Texture Quantification in 4D Dual Energy CT for Pulmonary Embolism Diagnosis, in: MICCAI workshop MCBR-CDS 2012, Nice, France, Seiten 45-56, 2013 |
[URL] |
| , , und , Enhanced visualization of pulmonary perfusion in 4D Dual Energy CT images, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA, Seiten 6710-6713, 2014 |
[DOI] |
, , , , 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 , How to find the best radiomics features for prediction of overall survival in SBRT for hepatocellular carcinoma?, in: European SocieTy for Radiotherapy & Oncology, 2019 |
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, , , , , , , , , und , Cleaning Radiotherapy Contours for Radiomics Studies, is it Worth it? A Head and Neck Cancer Study (2022), in: Clinical and Translational Radiation Oncology, 33(153-158)
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| , , , , , und , Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, Seiten 59-68, Springer LNCS, 2021 |
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| , , , , , und , Comparison of feature selection in radiomics for the prediction of overall survival after radiotherapy for hepatocellular carcinoma, in: IEEE Engineering in Medicine and Biology Conference, 2020 |
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| , , , , , , , und , Holographic visualisation and interaction of fused CT, PET and MRI volumetric medical imaging data using dedicated remote GPGPU ray casting, in: Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation, Seiten 102-110, Springer International Publishing, 2018 |
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| , und , A web interface for 3D information retrieval with images from the lung, in: Medinfo 2010, Cape Town, South Africa, 2010 |
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| , , , , , , , , , , und , Holistic Classification of CT Attenuation Patterns for Interstitial Lung Diseases via Deep Convolutional Neural Networks, in: 1st Workshop on Deep Learning in Medical Image Analysis, Münich, Germany, Seiten 41-48, 2015 |
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| , , , und , Integrating radiomics into holomics for personalised oncology: from algorithms to bedside (2020), in: European Radiology Experimental, 4(11) |
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| , , , , , , , , , , , , , , und , A Global Taxonomy of Interpretable AI: Unifying the Terminology for the Technical and Social Sciences (2022), in: Artificial Intelligence Review, 56(3473–3504) |
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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 , 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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