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
- data mining
- Desktop Grid
- Discrete wavelet transform
- eHealth
- Epilepsy
- ethnomethodology
- evaluation
- feature extraction
- FOS: Computer and information sciences
- fracture retrieval
- Grid
- Hadoop
- head and neck cancer
- HealthGrid
- High-resolution lung CT
- Hospital
- 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
- 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
- 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 Titel
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und , Sensors, Medical Images and Signal Processing: Exploring Multi--Dimensional Medical Data (2009), in: IMIA Yearbook of Medical Informatics, 4:1(81-83)
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| und , Sensors, Medical Images and Signal Processing: The Growth of Clinicians’ Expectations (2011), in: IMIA Yearbook of Medical Informatics, 6:1(92--95) |
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, und , Sensors, Medical Images and Signal Processing: Ubiquitous Personalized Health Monitoring (2012), in: IMIA Yearbook of Medical Informatics, 7:1(100-103)
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, , , , , , , und , Signature of Survival: A 18F-FDG PET Based Whole-Liver Radiomics Analysis Predicts Survival After 90Y-TARE for Hepatocellular Carcinoma (2017), in: OncoTarget, 9:4(4549-4558)
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| , , , und , Solid Spherical Energy (SSE) CNNs for Efficient 3D Medical Image Analysis, in: Irish Machine Vision and Image Processing Conference, Seiten 37-44, 2019 |
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| , , , , , , und , Standardised convolutional filtering for radiomics, 2020 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)
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, , , , und , Steer'n'Detect: Fast 2D Template Detection with Accurate Orientation Estimation (2022), in: Bioinformatics, 38:11(3146–3148)
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, , und , Steerable Wavelet Machines (SWM): Learning Moving Frames for Texture Classification (2017), in: IEEE Transactions on Image Processing, 26:4(1626-1636)
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| , , , , , , , , und , 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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| , , , , und , Synchronized slice viewing of similar image series, in: SPIE Medical Imaging: Advanced PACS-based Imaging Informatics and Therapeutic Applications, San Diego, CA, USA, Seiten 83190K, 2012 |
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| , , , , , , , , und , Task-Based Anthropomorphic CT Phantom for Radiomics Stability and Discriminatory Power Analyses (CT-Phantom4Radiomics), [Data set], 2023 |
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| , , , und , Text- and content-based medical image retrievals in the VISCERAL retrieval benchmark, Springer, 2017 |
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| , , und , Texture classification of anatomical structures in CT using a context-free machine learning approach, in: SPIE Medical Imaging 2015, Seiten 94140W-94140W-14, SPIE, 2015 |
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| , , , , und , Texture Quantification in 4D Dual Energy CT for Pulmonary Embolism Diagnosis, in: MICCAI workshop MCBR-CDS 2012, Nice, France, Seiten 45-56, 2013 |
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| , , , und , Texture-Based Computational Models of Biomedical Tissue in Radiological Images: Unveiling the Invisible, in: 14th Annual Symposium on Biomedical Computation at Stanford, Stanford, CA, USA, 2014 |
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, und , Texture-Driven Parametric Snakes for Semi-Automatic Image Segmentation (2019), in: Computer Vision and Image Understanding, 188(102793)
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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 , The Image Biomarker Standardisation Initiative (IBSI) On Reproducible Convolutional Radiomics, in: European Society of Radiology, 2022 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights (2024), in: Radiology, 310:2
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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 , The medGIFT project: perspective of a medical doctor (2007), in: Japanese Journal of Medical Imaging Technology, 25:5(356-361) |
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, , , , , , , , , und , The Use of Texture Based Radiomics CT Analysis to Predict Outcomes in Early-Stage Non-Small Cell Lung Cancer Treated with Stereotactic Ablative Radiotherapy (2018), in: The British Journal of Radiology, 92:1094(20180228)
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| , , , , , , und , The value of AI for assessing longitudinal brain metastases treatment response (2025), in: Neuro-Oncology Advances |
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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 , Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities (2014), in: Medical Image Analysis, 18:1(176-196)
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| , , , und , Using MapReduce for Large-scale Medical Image Analysis (2015), in: arXiv:1510.06937 |
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| , , , und , Using MapReduce for Large–scale Medical Image Analysis, in: 2nd IEEE Conference on Healthcare Informatics, Imaging and Systems Biology (HISB), La Jolla, California, 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 , USYD/HES-SO in the VISCERAL Retrieval Benchmark, in: ECIR workshop on Multimodal Retrieval in the Medical Domain, Vienna, Austria, Springer Lecture Notes in Computer Science (LNCS), 2015
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| , , , , , , , , und , Valeur de la TEP au 18-FDG pour prédire la récidive dans les cancers ORL non oropharyngé traités par radio-chimiothérapie, in: Société Française de radiothérapie Oncologique, 2017 |
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| , 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 , Web-Based Tools for Exploring the Potential of Quantitative Imaging Biomarkers in Radiology: Intensity and Texture Analysis on the ePAD Platform, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, Seiten 379-410, Elsevier, 2017 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Why is the winner the best?, in: CVPR, 2023 |
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| , und , Wide kernels and their DCT compression in convolutional networks for nuclei segmentation (2023), in: Informatics in Medicine Unlocked, 43(101403) |
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| , und , Yearbook 2012 section article, Yearbook of Medical Informatics, 2012 |