A5028616268- Radiomics and Machine Learning in Medical Imaging
- Functional Brain Connectivity Studies
- Scientific Computing and Data Management
- Medical Imaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Neural dynamics and brain function
- AI in cancer detection
- Traumatic Brain Injury Research
- Lung Cancer Diagnosis and Treatment
- Parkinson's Disease Mechanisms and Treatments
- Multimedia Communication and Technology
- Coastal and Marine Management
- Cell Image Analysis Techniques
- Neurological disorders and treatments
- Digital Radiography and Breast Imaging
- Botulinum Toxin and Related Neurological Disorders
- Pleural and Pulmonary Diseases
- Social Media in Health Education
- Advanced Biosensing Techniques and Applications
- EEG and Brain-Computer Interfaces
- Ultrasound in Clinical Applications
- Software System Performance and Reliability
- Sleep and Wakefulness Research
- Osteomyelitis and Bone Disorders Research
University of Lübeck
2024
Massachusetts General Hospital
2022
Photon Imaging (United States)
2022
University of Pittsburgh Medical Center
2020
Centre Hospitalier Universitaire de Liège
2017
University of Liège
2011-2016
Centre hospitalier régional de la Citadelle
2016
Cyclotron (Netherlands)
2011-2013
University of Gothenburg
2010
Abstract The National Cancer Institute (NCI) Research Data Commons (CRDC) aims to establish a national cloud-based data science infrastructure. Imaging (IDC) is new component of CRDC supported by the Moonshot. goal IDC enable broad spectrum cancer researchers, with and without imaging expertise, easily access explore value deidentified support integrated analyses nonimaging data. We achieve this colocating versatile collections computing resources exploration, visualization, analysis tools....
During non-rapid eye movement (NREM) sleep, a global decrease in synaptic strength associated with slow waves (SWs) would enhance signal-to-noise ratio of neural responses during subsequent wakefulness. To test this prediction, 32 human volunteers were trained to coarse orientation discrimination task, either the morning or evening. They retested after 8 h wakefulness respectively. Performance was enhanced only night absence any change abundance NREM SWs but proportion number "initiated"...
PURPOSE Zero-footprint Web architecture enables imaging applications to be deployed on premise or in the cloud without requiring installation of custom software user’s computer. Benefits include decreased costs and information technology support requirements, as well improved accessibility across sites. The Open Health Imaging Foundation (OHIF) Viewer is an extensible platform developed leverage these benefits address demand for open-source Web-based applications. can modified site-specific...
In Parkinson's disease (PD) the demonstration of neuropathological disturbances in nigrostriatal and extranigral brain pathways using magnetic resonance imaging remains a challenge. Here, we applied novel diffusion-weighted approach-track density (TDI). Twenty-seven non-demented patients (mean duration: 5 years, mean score on Hoehn & Yahr scale=1.5) were compared with 26 elderly controls matched for age, sex, education level. Track images created by sampling each subject's spatially...
Abstract A vast body of literature exists showing functional and structural dysfunction within the brains patients with disorders consciousness. However, function (fluorodeoxyglucose FDG‐PET metabolism)–structure (MRI‐diffusion‐weighted images; DWI) relationship how it is affected in severely brain injured remains ill‐defined. MRI‐DWI 25 (19 Disorders Consciousness which 7 unresponsive wakefulness syndrome, 12 minimally conscious; 6 emergence from conscious state) healthy control subjects...
To reduce head movement during resting state functional magnetic resonance imaging, post-coma patients with disorders of consciousness (DOC) are frequently sedated propofol. However, little is known about the effects this sedation on brain connectivity patterns in damaged essential for differential diagnosis. In study, we aimed to assess these effects.Using imaging 3T data obtained over several years scanning diagnostic and research purposes, employed a seed-based approach examine...
Accurate assessment of lymph node size in 3D CT scans is crucial for cancer staging, therapeutic management, and monitoring treatment response. Existing state-of-the-art segmentation frameworks medical imaging often rely on fully annotated datasets. However, segmentation, these datasets are typically small due to the extensive time expertise required annotate numerous nodes scans. Weakly-supervised learning, which leverages incomplete or noisy annotations, has recently gained interest...
Abstract Oncology clinical trials have become increasingly dependent upon image-based surrogate endpoints for determining patient eligibility and treatment efficacy. As therapeutics evolved multiplied in number, the tumor metrics criteria used to characterize therapeutic response progressively more varied complex. The growing intricacies of evaluation, together with rising expectations rapid consistent results reporting, make it difficult site radiologists adequately address local...
Purpose: XNAT is an informatics software platform to support imaging research, particularly in the context of large, multicentre studies type that are essential validate quantitative biomarkers. provides import, archiving, processing and secure distribution facilities for image related study data. Until recently, however, modern data visualisation annotation tools were lacking on platform. We describe background to, implementation of, integration Open Health Imaging Foundation (OHIF) Viewer...
Objective: To assess the effectiveness of soft splints on spasticity and hand opening in chronic patients with upper limb disorders consciousness (vegetative state/unresponsive wakefulness syndrome-VS/UWS minimally conscious state-MCS).Methods: In this prospective single-blind controlled trial, a blind evaluator assessed (Modified Ashworth Scale Modified Tardieu Scale), range motion (ROM) at metacarpophalangeal, wrist elbow joints patients' before after splinting, manual stretching control...
Abstract Introduction Independent component analysis ( ICA ) has been extensively used for reducing task‐free BOLD fMRI recordings into spatial maps and their associated time‐courses. The spatially identified independent components can be considered as intrinsic connectivity networks ICN s) of non‐contiguous regions. To date, the patterns have analyzed with techniques developed volumetric data. Objective Here, we detail a graph building technique that allows these ICNs to theory. Methods...
Brain-derived neurotrophic factor (BDNF) modulates the pruning of synaptically silent axonal arbors. The Met allele BDNF gene is associated with a reduction in neurotrophin's activity-dependent release. We used diffusion-weighted imaging to construct structural brain networks for 36 healthy subjects known genotypes. Through permutation testing we discovered clear differences connection strength between carrying and those homozygotic Val allele. trained Gaussian process classifier capable...
Detecting signs of consciousness in patients a vegetative state/unresponsive wakefulness syndrome (UWS/VS) or minimally conscious state (MCS) is known to be very challenging. Plotkin et al. (2010) recently showed the possibility using breathing-controlled communication device with locked syndrome. We here aim test breathing-based "sniff controller" that could used as an alternative diagnostic tool evaluate response command severely brain damaged chronic disorders (DOC).Twenty-five DOC were...
Artificial Intelligence (AI) is increasingly becoming a tool to enhance various medical image analysis tasks with accuracies comparable expert clinicians. Computer assisted detection and diagnosis, segmentation registration have significantly benefited from AI. However, integration of AI into the clinical workflow has been slow due requirements for libraries that are specific each model, also environments centers. These challenges demonstrate need an AI-based solution can be integrated any...
Event Abstract Back to A finite-element reciprocity solution for EEG forward modeling with realistic individual head models Erik Ziegler1*, Sarah L. Chellappa1, Giulia Gaggioni1, Julien Q. Ly1, Gilles Vandewalle1, Elodie André1, Christophe Geuzaine2 and Phillips1, 2 1 University of Liege, Cyclotron Research Centre, Belgium Liège, Department Electrical Engineering Computer Science, We present a finite element modelling (FEM) implementation solving the problem in electroencephalography (EEG)....