A5015971484- EEG and Brain-Computer Interfaces
- Radiomics and Machine Learning in Medical Imaging
- Medical Image Segmentation Techniques
- Medical Imaging and Analysis
- Fractal and DNA sequence analysis
- Obstructive Sleep Apnea Research
- Epilepsy research and treatment
- Artificial Intelligence in Healthcare and Education
- Cerebral Venous Sinus Thrombosis
- Atrial Fibrillation Management and Outcomes
- Machine Learning in Healthcare
- Medical Imaging Techniques and Applications
- Heart Rate Variability and Autonomic Control
- Cardiac electrophysiology and arrhythmias
- ECG Monitoring and Analysis
- Advanced MRI Techniques and Applications
- MRI in cancer diagnosis
- Neural dynamics and brain function
Institute of Neurological Sciences
2024
Istituti di Ricovero e Cura a Carattere Scientifico
2024
Istituto delle Scienze Neurologiche di Bologna
2023-2024
National Research Council
2022
Istituto di Fisiologia Clinica
2022
Objectives To describe the occurrence of secondary sclerosing cholangitis in critically ill patients (SC-CIP) with febrile infection-related epilepsy syndrome (FIRES). Methods Monocentric retrospective analysis all adult FIRES admitted from January 2020 to December 2024. Results Four (3 males) a mean age 24 years (range: 18–40 years) and no significant medical history presented cryptogenic FIRES. They required treatment antiseizure medications (mean: 9; range: 8–10), anesthetics (propofol,...
Our work aims to exploit deep learning (DL) models automatically segment diagnostic regions involved in Alzheimer’s disease (AD) 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) volumetric scans order provide a more objective diagnosis of this and reduce the variability induced by manual segmentation. The dataset used study consists 102 volumes (40 controls, 39 with established (AD), 23 mild cognitive impairment (MCI)). ground truth was generated an expert user who...
Stereoelectroencephalography (SEEG) is an invasive surgical procedure to record the electrical activities in cortical brain regions, aiming at identifying Epileptogenic Zone (EZ) patients with drug-resistant epilepsy. To improve accuracy of EZ definition, SEEG analysis can be supported by computational tools, among which Index (EI) represents most common solution. However, scientific community has still not found agreement on quantitative biomarkers characterize sites within EZ. In this...
Abstract Purpose To determine the best kinetic model to be applied on dynamic brain [ 18 F]FDG PET images by characterizing regional glucose metabolism of normal Göttingen minipigs. Methods Nine minipigs were scanned with a clinical PET/CT tomograph, starting from injection an intravenous bolus F]FDG, for about 25 min. Dynamic reconstructed and nine regions interest (ROI), plus vascular region, defined time-activity curves (TAC) determined. Three models considered fitting experimental TACs:...