Keywords:
- 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
Publications of Adrien Depeursinge
2019
, and , Texture-Driven Parametric Snakes for Semi-Automatic Image Segmentation (2019), in: Computer Vision and Image Understanding, 188(102793)
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2018
| , , , , , and , (18F)-FDG PET/CT parameters to predict survival and recurrence in patients with locally advanced cervical cancer treated with chemoradiotherapy (2018), in: Cancer / Radiothérapie, 22:3(229-235) |
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| , , and , Fast Rotational Sparse Coding (2018)(arXiv:1806.04374) |
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| , , , , , , , and , 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, pages 102-110, Springer International Publishing, 2018 |
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| , , , , , , , , and , Locoregional radiogenomic models to capture gene expression heterogeneity in glioblastoma (2018), in: biorXiv |
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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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| , and , Rotation-Covariant Tissue Analysis for Interstitial Lung Diseases Using Learned Steerable Filters: Performance Evaluation and Relevance for Diagnostic Aid (2018), in: Computerized Medical Imaging and Graphics, 64(1-11) |
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| and , Rotational 3D Texture Classification Using Group Equivariant CNNs (2018), in: ArXiv |
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, , , , , , , , , and , 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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2017
| , , , , , , and , 18-FDG PET-CT parameters to predict survival and recurrence in cervical cancer patients treated with chemo-radiotherapy, in: European Society for Radiotherapy and Oncology, Vienna, 2017 |
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, , , and , 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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, , , , , , , , , , , , and , A PET-based nomogram for oropharyngeal cancers (2017), in: European Journal of Cancer, 75(222-230)
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| , , , , , , and , 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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| , and , Biomedical Texture Analysis: Fundamentals, Applications and Tools, Elsevier, Elsevier-MICCAI Society Book series, 2017 |
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| and , Biomedical Texture Operators and Aggregation Functions: A Methodological Review and User’s Guide, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 55-94, Elsevier, 2017 |
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| , , , , and , Comparing 18-FDG PET 3D texture attributes for the prediction of survival and recurrence in oropharyngeal cancers treated with radiotherapy, in: Workshop on the Prediction and Modeling of response to Molecular and External Beam Radiotherapies, Le Bono, France, 2017 |
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| , and , Fundamentals of Texture Processing for Biomedical Image Analysis: A General Definition and Problem Formulation, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 1-27, Elsevier, 2017 |
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, , , , , and , Metabolic Tumor Volume and Total Lesion Glycolysis in Oropharyngeal Cancer treated with definitive radiotherapy: Which threshold is the best predictor of local control ? (2017), in: Clinical Nuclear Medicine, 42:6(e281–e285)
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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, pages 29-53, Elsevier, 2017 |
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| , , , , , , , , and , Nouveaux paramètres métaboliques du FDG-PET/TDM pour prédire la récurrence et la survie des cancers du col utérin traité par radio-chimiothérapie, in: Société Française de radiothérapie Oncologique, 2017 |
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| , , , , , and , QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 349-377, Elsevier, 2017 |
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| , and , QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT, Demonstration at SPIE MI 2017, 2017 |
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, , , , , , , and , 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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, , and , 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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| , , , and , Text- and content-based medical image retrievals in the VISCERAL retrieval benchmark, Springer, 2017 |
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| , , , , , , , , and , 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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| , and , Visual Grammar: a language modelling approach for building efficient and meaningful bags of visual words (2017), in: ArXiv(1835004) |
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| , , , , and , 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, pages 379-410, Elsevier, 2017 |
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2016
, , , , , , , and , A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT (2016), in: IEEE Transactions on Medical Imaging, 35:12(2620-2630)
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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 , 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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| , , , , 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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| , and , Multidimensional Texture Analysis for Improved Prediction of Ultrasound Liver Tumor Response to Chemotherapy Treatment, in: Medical Image Computing and Computer-Assisted Interventions (MICCAI), pages 619--626, Springer International Publishing, 2016 |
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| , and , 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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, , , , , , , and , Overview of the predictive value of quantitative 18 FDG PET in head and neck cancer treated with chemoradiotherapy (2016), in: Critical Reviews in Oncology/Hematology, 108(40-51)
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2015
| , , , , , , and , 3D Riesz–wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 7909-7912, 2015 |
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, , , , , and , Automated Classification of Usual Interstitial Pneumonia using Regional Volumetric Texture Analysis in High-Resolution CT (2015), in: Investigative Radiology, 50:4(261-267)
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| , , , , , , , and , Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, pages 581-588, Springer International Publishing, 2015 |
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| , , and , 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, pages 31-35, CEUR-WS, 2015 |
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| , , and , Hierarchic Anatomical Structure Segmentation Guided by Spatial Correlations (AnatSeg-Gspac): VISCERAL Anatomy3, in: Proceedings of the VISCERAL Anatomy Grand Challenge at the 2015 IEEE ISBI, pages 22-26, CEUR-WS, 2015 |
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| , , , , , , , , , , and , 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, pages 41-48, 2015 |
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| , , , , , and , Optimized steerable wavelets for texture analysis of lung tissue in 3-D CT: classification of usual interstitial pneumonia, in: IEEE 12th International Symposium on Biomedical Imaging (ISBI), New York, NY, USA, pages 403-406, IEEE, 2015 |
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, , and , 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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| , , , , and , Predicting non-response to NAC in patients with breast cancer using 3D texture analysis, in: European Congress of Radiology, Vienna, Austria, 2015 |
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| , , , , and , Pulmonary Embolism Detection using Localized Vessel-Based Features in Dual Energy CT, in: SPIE Medical Imaging, pages 941407-941407-10, SPIE, 2015 |
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| , , , , and , Quantitative Image Texture Analysis Predicts Malignancy on Multiparametric Prostate MRI, in: 91st Annual Meeting of the Western Section of American Urological Association, Indian Wells, CA, USA, 2015 |
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| , , and , Texture classification of anatomical structures in CT using a context-free machine learning approach, in: SPIE Medical Imaging 2015, pages 94140W-94140W-14, SPIE, 2015 |
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