A5041375630- Biomedical Text Mining and Ontologies
- Semantic Web and Ontologies
- Medical Image Segmentation Techniques
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Image Retrieval and Classification Techniques
- Advanced MRI Techniques and Applications
- Social Policies and Family
- Digital Radiography and Breast Imaging
- Scientific Computing and Data Management
- Social Sciences and Governance
- AI in cancer detection
- Advanced Neuroimaging Techniques and Applications
- Anatomy and Medical Technology
- Surgical Simulation and Training
- Augmented Reality Applications
- Functional Brain Connectivity Studies
- Advanced X-ray and CT Imaging
- Distributed and Parallel Computing Systems
- Medical Imaging and Analysis
- French Urban and Social Studies
- Artificial Intelligence in Healthcare and Education
- Colorectal Cancer Screening and Detection
- Radiology practices and education
- Radiation Dose and Imaging
Université de Rennes
2012-2025
Inserm
2012-2025
Laboratoire Traitement du Signal et de l'Image
2012-2022
Centre Hospitalier Universitaire de Rennes
2022
Metropolitan University
2018
Institut de Recherche Technologique B-com
2018
Institut National de Recherche en Santé Publique
2015
Karlsruhe Institute of Technology
2015
Institut national de recherche en informatique et en automatique
2007-2012
Centre National de la Recherche Scientifique
2007-2012
Although numerous methods to register brains of different individuals have been proposed, no work has done, as far we know, evaluate and objectively compare the performances nonrigid (or elastic) registration on same database subjects. In this paper, propose an evaluation framework, based global local measures relevance registration. We chosen focus more particularly matching cortical areas, since intersubject are dedicated anatomical functional normalization, also because other groups shown...
In Surgical Data Science (SDS), there is an increasing demand for large, realistic annotated datasets to facilitate the development of machine learning techniques. However, in laparoscopic surgery, most publicly available focus on low-granularity procedural annotations (such as phases or steps) and image segmentation instruments specific organs, often using animal models that lack clinical realism. Furthermore, annotation variability seldom evaluated. this work, we compiled 30 sleeve...
This paper presents the Virtual Imaging Platform (VIP), a platform accessible at http://vip.creatis.insa-lyon.fr to facilitate sharing of object models and medical image simulators, provide access distributed computing storage resources. A complete overview is presented, describing ontologies designed share in common repository, workflow template used integrate tools strategies exploit Simulation results obtained four modalities with different show that VIP versatile robust enough support...
Object. The authors present the use of cortical sulci, segmented from magnetic resonance (MR) imaging, and functional data (f)MR imaging magnetoencephalography (MEG) in image-guided surgical management lesions adjacent to sensorimotor cortex. Methods. In an initial set 11 patients, sulci near were automatically MR sets, then MEG fMR examinations performed. Relevant information was preoperatively interpreted selected subsequently transferred navigation system for sulci. A neuronavigation...
Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology a controlled structured vocabulary consisting general terms (such as "cell" or "image" "tissue" "microscope") that form the basis such These are designed to represent types entities in domain reality has been devised capture; provided with logical definitions thereby also supporting reasoning over tagged data.This paper provides survey biomedical imaging ontologies have...
Objective: Improvement of the planning stage image-guided surgery requires a better anticipation surgical procedure and its anatomical functional environment. This should be provided by acquisition multimodal medical images patient understanding procedures. In this paper, we propose improvements to performance neurosurgery through use information models related neurosurgical procedures.Materials Methods: A new generic model procedures is introduced in context craniotomies. The basic...
Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack relevant ground truth. We propose a methodology generate MRI SPECT dedicated illustrate method when dealing with ictal SPECT. The consists generating or data perfectly aligned high-resolution 3D T1-weighted using realistic Monte Carlo simulations that closely reproduce response imaging system. Anatomical input are obtained from this MRI, while...