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
- 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
Publications of Adrien Depeursinge sorted by title
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| , , , , , , , , , and , 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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| , and , Region-based volumetric medical image retrieval, in: SPIE Medical Imaging: Advanced PACS-based Imaging Informatics and Therapeutic Applications, Orlando, FL, USA, pages 867406-867406-10, SPIE, 2013 |
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| , , , , , and , 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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, , , , , and , 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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| , , , , , , 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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, and , 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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| , , , , , , , , 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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, , , , , and , 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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| , , , 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 texture analysis of 4D dual-energy CT as an indicator of local pulmonary perfusion, in: IEEE 10th International Symposium on Biomedical Imaging, San Francisco, CA, USA, pages 149-152, IEEE, 2013 |
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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 , Rotation-covariant visual concept detection using steerable Riesz wavelets and bags of visual words, in: SPIE Wavelets and Sparsity XV, San Diego, CA, USA, pages 885816-885816-11, SPIE, 2013 |
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| , and , Rotation-invariant non-local means based on Riesz pyramid features and SURE parameter selection, in: 84th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM 2013), Novi Sad, Serbia, 2013 |
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, , and , Rotation–covariant texture learning using steerable Riesz wavelets (2014), in: IEEE Transactions on Image Processing, 23:2(898-908)
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| and , Rotational 3D Texture Classification Using Group Equivariant CNNs (2018), in: ArXiv |
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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 , Sensors, Medical Images and Signal Processing: Comprehensive Multi--modal Diagnosis Aid Frameworks (2010), in: IMIA Yearbook of Medical Informatics, 5:1(43--46)
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and , 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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| and , 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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, and , 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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, , , , , , , 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 , 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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| , , , , , , and , Standardised convolutional filtering for radiomics, 2020 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)
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, , , , and , Steer'n'Detect: Fast 2D Template Detection with Accurate Orientation Estimation (2022), in: Bioinformatics, 38:11(3146–3148)
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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 , 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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| , , , , and , Synchronized slice viewing of similar image series, in: SPIE Medical Imaging: Advanced PACS-based Imaging Informatics and Therapeutic Applications, San Diego, CA, USA, pages 83190K, 2012 |
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| , , , , , , , , and , Task-Based Anthropomorphic CT Phantom for Radiomics Stability and Discriminatory Power Analyses (CT-Phantom4Radiomics), [Data set], 2023 |
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| , , , and , Teaching Radiomics through an Interactive Platform: A Qualitative Study on the Use of QuantImage in Medical Education, European Society of Medical Imaging Informatics (EuSoMII), 2025 |
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| , , , and , Text- and content-based medical image retrievals in the VISCERAL retrieval benchmark, Springer, 2017 |
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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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| , , , , and , Texture Quantification in 4D Dual Energy CT for Pulmonary Embolism Diagnosis, in: MICCAI workshop MCBR-CDS 2012, Nice, France, pages 45-56, 2013 |
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| , , , and , 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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, and , Texture-Driven Parametric Snakes for Semi-Automatic Image Segmentation (2019), in: Computer Vision and Image Understanding, 188(102793)
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, , , , , , , , , , , , , , , , , , , , and , The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information, 2025
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, , , , , , , , and , 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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| , , , , , and , The Image Biomarker Standardisation Initiative (IBSI) On Reproducible Convolutional Radiomics, in: European Society of Radiology, 2022 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights (2024), in: Radiology, 310:2
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, , , , and , The Importance of Feature Aggregation in Radiomics: A Head and Neck Cancer Study (2020), in: Nature Scientific Reports, 10:19679
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| , , , , and , The medGIFT project: perspective of a medical doctor (2007), in: Japanese Journal of Medical Imaging Technology, 25:5(356-361) |
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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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| , , , , , , and , The value of AI for assessing longitudinal brain metastases treatment response (2025), in: Neuro-Oncology Advances, 7:1 |
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| , , and , Three dimensional multi–scale visual words for texture–based cerebellum segmentation, in: Medical Imaging 2012: Image Processing, San Diego, CA, USA, pages 83142Z, SPIE, 2012 |
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, , and , Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities (2014), in: Medical Image Analysis, 18:1(176-196)
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| , , , and , Unraveling AI imaginaries in radiomics: Beyond exoticism, mentalism, and technologism, 10th STS Italia Conference - Technoscience for Good: Designing, Caring, and Reconfiguring, 2025 |
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| , , , and , Using MapReduce for Large-scale Medical Image Analysis (2015), in: arXiv:1510.06937 |
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| , , , and , 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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| , and , Using Multiscale Visual Words for Lung Texture Classification and Retrieval, in: Medical Content-based Retrieval for Clinical Decision Support, Toronto, Canada, pages 69-79, Lecture Notes in Computer Sciences (LNCS), 2012 |
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