A5036277512- Radiomics and Machine Learning in Medical Imaging
- Advanced X-ray and CT Imaging
- COVID-19 diagnosis using AI
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Medical Imaging Techniques and Applications
- Radiation Dose and Imaging
- Functional Brain Connectivity Studies
- Lung Cancer Diagnosis and Treatment
- Epilepsy research and treatment
- Meningioma and schwannoma management
- Digital Radiography and Breast Imaging
- Radiation Detection and Scintillator Technologies
- Urban Planning and Landscape Design
- Nuclear Physics and Applications
- Ancient Mediterranean Archaeology and History
- Brain Metastases and Treatment
- Medical Imaging and Analysis
- EEG and Brain-Computer Interfaces
- Air Quality Monitoring and Forecasting
- Urban Planning and Valuation
- Neurobiology of Language and Bilingualism
- Foreign Language Teaching Methods
- Action Observation and Synchronization
- Brain Tumor Detection and Classification
Azienda Ospedaliera Citta' della Salute e della Scienza di Torino
2024-2025
Azienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda
2018-2024
Ospedale Maggiore
2018-2023
Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia
2013-2014
Istituto Nazionale di Fisica Nucleare, Sezione di Torino
2008
Abstract Background The role of computed tomography (CT) in the diagnosis and characterization coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated performance a software for quantitative analysis chest CT, LungQuant system, by comparing its results with independent visual evaluations group 14 clinical experts. aim this work is to evaluate ability automated tool extract information from lung relevant design support model. Methods segments both lungs lesions...
Abstract Background To develop a pipeline for automatic extraction of quantitative metrics and radiomic features from lung computed tomography (CT) artificial intelligence (AI) models supporting differential diagnosis between coronavirus disease 2019 (COVID-19) other viral pneumonia (non-COVID-19). Methods Chest CT 1,031 patients (811 model building; 220 as independent validation set (IVS) with positive swab severe acute respiratory syndrome coronavirus-2 (647 COVID-19) or viruses (384...
To assess the impact of lung segmentation accuracy in an automatic pipeline for quantitative analysis CT images.Four different platforms based on convolutional neural network (CNN), region-growing technique and atlas-based algorithm were considered. The tested using images 55 COVID-19 patients with severe impairment. Four radiologists assessed segmentations a 5-point qualitative score (QS). For each series, manually revised reference (RS) was obtained. Histogram-based metrics (QM) calculated...
Growing evidence suggests that artificial intelligence tools could help radiologists in differentiating COVID-19 pneumonia from other types of viral (non-COVID-19) pneumonia. To test this hypothesis, an R-AI classifier capable discriminating between and non-COVID-19 was developed using CT chest scans 1031 patients with positive swab for SARS-CoV-2 (
<b><i>Introduction:</i></b> The WHO declared 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a public health emergency of international concern. National and Regional Health System has been reorganized, many oncological patients died during this period or had to interrupt their therapies. This study summarizes single-centre experience, the COVID-19 in Italy, treatment brain metastases with Gamma Knife stereotactic radiosurgery (GKRS)....
<b>Background:</b> The use of the prone position (PP) has been widespread during COVID-19 pandemic. While it demonstrated benefits, including improved oxygenation and lung aeration, factors influencing response in terms gas exchange to PP remain unclear. In particular, association between baseline quantitative Computed Tomography (qCT) scan results intubated, mechanically ventilated subjects with ARDS is unknown. present study aimed compare qCT responding or carbon dioxide (CO<sub>2</sub>)...
Objective To optimize a dual-energy computed tomographic protocol with sinogram-affirmed iterative reconstruction algorithms for improving small nodules detection. Methods The raw data of arterial acquisition cirrhotic patient were reconstructed standard filtered back projection (B20f) and 3 (I26, I30, I31) kernels different strength (S3–S5). 80-kilovolt (peak) (kVp) the linear blended (DE_0.5) images (80–140 kVp) analyzed. For each series, 8-subcentimeter low-contrast lesions simulated...
Brain metastases are the most common brain tumors, being one of frequent neurological complications systemic cancer and an important cause morbidity mortality. Stereotactic radiosurgery is efficacious safe in treatment metastases, with good local control rates low adverse effects rate. Large present some issues balancing treatment-related toxicity.Demonstrating adaptive staged-dose Gamma Knife (ASD-GKRS) a effective for large metastases.We retrospectively analyzed our series patients treated...
Language lateralization in patients with focal epilepsy frequently diverges from the left-lateralized pattern that prevails healthy right-handed people, but mechanistic explanations are still a matter of debate. Here, we debate complex interaction between epilepsy, language lateralization, and functional neuroimaging techniques by introducing case patient unaware seizures preceded aphasia, whom video-EEG PET examination suggested presence cortical dysplasia right superior temporal gyrus,...