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 Zeitschrift und Typ
Journal of Digital Imaging
, , , , , , und , Comparative Performance Analysis of State-of-the-Art Classification Algorithms Applied to Lung Tissue Categorization (2010), in: Journal of Digital Imaging, 23:1(18-30)
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Journal of Imaging
| , und , Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop (2016), in: Journal of Imaging, 2:2(19) |
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Journal of Medical Imaging
| , und , Neural Network Training for Cross-Protocol Radiomic Feature Standardization in Computed Tomography (2019), in: Journal of Medical Imaging, 6:3(024008) |
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| , , , , , , und , Assessing Treatment Response in Triple Negative Breast Cancer from Quantitative Image Analysis in Perfusion MRI (2017), in: Journal of Medical Imaging, 5:1(5-10) |
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Journal of Nuclear Medicine
, , , , , , , , , und , FDG-PET/CT-based prognostic survival model after surgery for head and neck cancer (2022), in: Journal of Nuclear Medicine, 63:1
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| , , , , , , und , Impact of a Gaussian filter applied to post-reconstruction PET images on radiomic features to predict complete pathological response in breast cancer (2020), in: Journal of Nuclear Medicine, 61:supplement 1(606--606) |
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| , , , , , , und , Impact of a Gaussian filter applied to post-reconstruction PET on radiomic features in assessing tumor heterogeneity in breast cancer. (2020), in: Journal of Nuclear Medicine, 61:supplement 1(612--612) |
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| , , , , und , PET/CT Radiomics predict Pulmonary Lymphangitic Carcinomatosis (PLC) in Non-Small Cell Lung Cancer (NSCLC) (2020), in: Journal of Nuclear Medicine, 61:supplement 1(1311--1311) |
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Market/IBCom
| und , La recherche d’images en plusieurs dimensions (2011), in: Market/IBCom |
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Medical Image Analysis
, , , , , , , , , , und , Automatic Head and Neck Tumor Segmentation and Outcome Prediction Relying on FDG-PET/CT Images: Findings from the Second Edition of the HECKTOR Challenge (2023), in: Medical Image Analysis, 90:1(102972)
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, , , , , , , , , , , , , , , , , , , , , , , , , und , Head and Neck Tumor Segmentation in PET/CT: The HECKTOR Challenge (2022), in: Medical Image Analysis, 77(102336)
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, , , und , Local Rotation Invariance in 3D CNNs (2020), in: Medical Image Analysis, 65(101756)
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, , und , Fusing Learned Representations from Riesz and Deep CNNs for Lung Tissue Classification (2019), in: Medical Image Analysis, 56(172-183)
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, , und , Automated Classification of Brain Tumor Type in Whole-Slide Digital Pathology Images Using Local Representative Tiles (2016), in: Medical Image Analysis, 30(60-71)
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, , , und , On combining visual and ontological similarities for medical image retrieval applications (2014), in: Medical Image Analysis, 18:7(1082–1100)
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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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Medical Physics
| , , , , , , , , , , , und , 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 |
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, , , , , , , und , 3D-Printed Iodine-Ink CT Phantom for Radiomics Feature Extraction - Advantages and Challenges (2023), in: Medical Physics, 50:9(5682-5697)
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, , 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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Multimedia Tools and Applications
, 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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Multiple Sclerosis Journal
| , , , , , , , , , , , , und , A multi-modal deep learning network for the classification of paramagnetic rim and remyelinated lesions in multiple sclerosis (2026), in: Multiple Sclerosis Journal |
Nature Scientic Reports
| , , , , , , , , und , Automatic Detection and Multi-Component Segmentation of Brain Metastases in Longitudinal MRI (2024), in: Nature Scientic Reports, 14:1(1-10) |
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Nature Scientific Reports
| , , , , , , , und , Instance-level quantitative saliency in multiple sclerosis lesion segmentation (2026), in: Nature Scientific Reports |
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| , , , , , , , , , und , Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction (2024), in: Nature Scientific Reports, 14:9644 |
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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 , Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness (2019), in: Nature Scientific Reports, 9:1(4500)
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Neuro-Oncology Advances
| , , , , , , , , , und , RDTA-08 MULTI-SEQUENTIAL STEREOTACTIC RADIOSURGERY (SRS) FOR BRAIN METASTASES: 10-YEAR EXPERIENCE FROM THE CHUV (LAUSANNE, SWITZERLAND) BRAIN METASTASIS CLINIC (2025), in: Neuro-Oncology Advances, 7:Supplement_2(ii26-ii26) |
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| , , , , , , und , The value of AI for assessing longitudinal brain metastases treatment response (2025), in: Neuro-Oncology Advances, 7:1 |
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Neurodegenerative Diseases
| , , , , , , , , , , , , und , A radiomics-based analysis of functional dopaminergic scintigraphic imaging for the diagnosis of dementia with Lewy bodies (2025), in: Neurodegenerative Diseases |
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NeuroImage: Clinical
, , , , , , und , How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review (2023), in: NeuroImage: Clinical, 39(103491)
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OncoTarget
, , , , , , , 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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Pattern Recognition Letters
, und , Hierarchical classification using a frequency-based weighting and simple visual features (2008), in: Pattern Recognition Letters, 29:15(2011-2017)
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Philippine Journal of Information Technology
| , , und , A Medical Image Retrieval Application Using Grid Technologies To Speed Up Feature Extraction in Medical Image Retrieval (2009), in: Philippine Journal of Information Technology |
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Plos One
Radiology
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , 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 , Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)
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Scientific Reports
, , , , , , , , und , Assessing radiomics feature stability with simulated CT acquisitions (2022), in: Scientific Reports, 12:1(4732)
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Special Issue "Interpretable and Annotation-Efficient Learning for Medical Image Computing" in Machine Learning and Knowledge Extraction
| , , , 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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Swiss Medical Informatics
| , , , , , und , A framework for diagnosing interstitial lung diseases in HRCT : the TALISMAN project (2008), in: Swiss Medical Informatics, 64(17-20) |
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| , , , , und , How clinical information systems can support life science research (2008), in: Swiss Medical Informatics, 64(21-24) |
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The British Journal of Radiology
, , , , , , , , , 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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The Open Medical Informatics Journal (TOMIJ)
| , , und , Prototypes for content-based image retrieval in clinical practice (2011), in: The Open Medical Informatics Journal (TOMIJ), 5(58-72) |
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Yearbook of Medical Informatics
, , , , und , Clinical Data Mining: a Review (2009), in: Yearbook of Medical Informatics(121-133)
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Publikationen vom Typ Book
2017
| , und , Biomedical Texture Analysis: Fundamentals, Applications and Tools, Elsevier, Elsevier-MICCAI Society Book series, 2017 |
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Publikationen vom Typ Inbook
| , , , und , Text- and content-based medical image retrievals in the VISCERAL retrieval benchmark, Springer, 2017 |
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2012
| , und , Yearbook 2012 section article, Yearbook of Medical Informatics, 2012 |
Publikationen vom Typ Incollection
2017
| und , Biomedical Texture Operators and Aggregation Functions: A Methodological Review and User’s Guide, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, Seiten 55-94, Elsevier, 2017 |
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| , und , Fundamentals of Texture Processing for Biomedical Image Analysis: A General Definition and Problem Formulation, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, Seiten 1-27, Elsevier, 2017 |
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| , Multi-Scale and Multi-Directional Biomedical Texture Analysis: Finding the Needle in the Haystack, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, Seiten 29-53, Elsevier, 2017 |
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