1,721,099 research outputs found
Explaining Network Decision Provides Insights on the Causal Interaction Between Brain Regions in a Motor Imagery Task
No full textNeural decoding widely exploits machine learning for classifying electroencephalographic (EEG) signals for brain-computer interface applications. Recent advancements in neural decoding regards the use of brain functional connectivity estimates as input features and the adoption of convolutional neural networks (CNNs) to realize decoders. Moreover, explainable artificial intelligence (XAI) approaches based on CNNs are growing interest in the neuroscience community, for validating the knowledge learned by networks and for using the decoder not only to classify the EEG but also to analyze it in a data-driven way, without a priori assumptions. However, the adoption of connectivity estimates for neural decoding is still in its infancy, as adopts non-directed connectivity measures, limits the analysis of few interactions/frequency ranges, and exploits classic machine learning approaches without exploring CNNs. Moreover, XAI approaches have never been applied to analyze EEG-based functional connectivity. To overcome these limitations, we design and apply a CNN for processing directed connectivity measures estimated via spectral Granger causality. The CNN automatically learns features in the frequency and spatial domains, and it is coupled with an explanation technique (DeepLIFT) for highlighting the most relevant connectivity inflow and outflow associated to each decoded brain state. Our approach is applied to motor imagery decoding, and achieves state-of-the-art performance compared to existing networks. DeepLIFT relevance representations match the directional interactions known occurring when imagining movements, validating the features related to the brain network, as learned by the CNN
Ruolo della Risonanza Magnetica nella staziazione e nel follow-up delle neoplasie laringee
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Treatment monitoring of paranasal sinus tumors by magnetic resonance imaging
No full textTreatment monitoring of paranasal tumors is crucial, given the high rate of local and regional relapses that impairs the overall prognosis of patients. Magnetic resonance imaging (MRI) is the technique of choice to detect changes in the submucosa and deep spaces of the suprahyoid neck, inaccessible at clinical and endoscopic assessment. Correct interpretation of MRI requires detailed knowledge of the treatment applied and of the changes treatments are supposed to produce on macroscopic anatomy and tissue signals. Once such background of information is obtained, detection of recurrences is a less challenging task
Imaging Methods: General Principles
No full textImaging plays a central role in the management of patients affected by aortitis, from the confirmation of the diagnosis to its follow-up over time. Giant cell arteritis, is a chronic idiopathic granulomatous vasculitis and represents the most common form of aortitis. Takayasu’s arteritis is a rare form of vasculitis, typically affects female at the third decade of life. Chronic periaortitis is a rare vascular and connective inflammatory disease which comprises a spectrum of conditions; it is more prevalent in the male aged between 40 and 60 years. Infectious aortitis have high mortality and morbidity; in most cases, it is caused by bacterial infections and occurs in patients with pre-existing aortic wall pathology. Almost any imaging modality can be used in the evaluation of aortitis and vasculitis of the great vessels. The various techniques, each with their inherent advantages and limitations, provide valuable and often complementary information
Solitary fibrous tumour of the supraglottic larynx.
Full text linkSolitary fibrous tumour (SFT) is a rare, benign, mesenchymal neoplasm that usually arises in the pleura, but rarely involves other sites outside the serosal space (mediastinum, lung, liver, thyroid gland); larynx involvement is very rare with only sporadic cases reported in the literature. We report a case of SFT in a 41-year-old woman with supraglottic laryngeal invovlement; symptoms included dysphonia and mild odynophagia lasting 2 years, and fibre-optic laryngeal evaluation showed a sub-mucosal mass involving the left supraglottis and medial wall of the pyriform sinus. MRI represents the gold standard tool for differential diagnosis (with schwannoma, paraganglioma and haemangioma) and correct staging, while immunohistochemical and cytomorphologic analysis (bcl-2 and CD34 positivity in 90% of cases) is needed for definitive diagnosis. Surgery is the main treatment (endoscopic and open conservative technique), and its goal is a balance between safe oncological resection and good preservation of laryngeal functions; in this particular case an open laryngeal approach was scheduled due to the size of the tumour. Prognosis is good and in only a few cases (especially in pleural SFT) does the biological behaviour take a malignant course
A complete fos approach for indoor crowdsourced mapping. Case study on Sapienza University of Rome faculties
Full text linkIndoor mapping is an essential process in several applications such as the visualization of space and its utilization, security and resource planning, emergency planning and location-based alerts and, last but not least, indoor navigation. In this work, a completely free and open-source (FOS) approach to map indoor environments, and to navigate through them, is presented. Our tests were carried out within Sapienza University of Rome public buildings; in detail, Letters and Philosophy faculty and Engineering faculty indoor environments were mapped. To reach this goal, only open source software such as Quantum GIS (QGIS) and open-source platforms like Open Street Map (OSM) and its indoor viewer, Open Level Up (OLU) were adopted. A database of indoor environments of the two faculties, completely compatible with OLU, was created through QGIS. In this way, a public territorial information system of classrooms, offices and laboratories is accessible to everyone who can, hence, add or modify the information, following the principle of crowdsourcing and of Volunteered Geographic Information (VGI). The developed procedure is now standard and its outputs accepted by the OSM community. Hence, the long-term developments of this project are the proposal for the volunteered and cooperative indoor mapping and design of strategic buildings and infrastructures (hospitals, schools, public offices, shopping centers, stations, airports etc.), starting from the available information (indoor layouts) and knowledge acquired through experience of people who normally work inside them and/or visit them frequently. In this context it is possible to state that the development of VGI for internal maps for strategic buildings, infrastructures and denied GNSS environments, not only supports and improves internal and external navigation without interruption, but can also have a significant positive impact on security and emergency management
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