19 resultados para Volitive modality


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Obiettivo: Valutare l’accuratezza reciproca dell’ecografia “esperta” e della risonanza magnetica nelle diagnosi prenatale delle anomalie congenite. Materiali e metodi: Sono stati retrospettivamente valutati tutti i casi di malformazioni fetali sottoposte a ecografia “esperta” e risonanza magnetica nel nostro Policlinico da Ottobre 2001 a Ottobre 2012. L’età gestazionale media all’ecografia e alla risonanza magnetica sono state rispettivamente di 28 e 30 settimane. La diagnosi ecografica è stata confrontata con la risonanza e quindi con la diagnosi postnatale. Risultati: sono stati selezionati 383 casi, con diagnosi ecografica o sospetta malformazione fetale “complessa” o anamnesi ostetrica positiva infezioni prenatali, valutati con ecografia “esperta”, risonanza magnetica e completi di follow up. La popolazione di studio include: 196 anomalie del sistema nervoso centrale (51,2%), 73 difetti toracici (19,1%), 20 anomalie dell’area viso-collo (5,2%), 29 malformazioni del tratto gastrointestinale (7,6%), 37 difetti genito-urinari (9,7%) e 28 casi con altra indicazione (7,3%). Una concordanza tra ecografia, risonanza e diagnosi postnatale è stata osservata in 289 casi (75,5%) ed è stata maggiore per le anomalie del sistema nervoso centrale 156/196 casi (79,6%) rispetto ai difetti congeniti degli altri distretti anatomici 133/187 (71,1%). La risonanza ha aggiunto importanti informazioni diagnostiche in 42 casi (11%): 21 anomalie del sistema nervoso centrale, 2 difetti dell’area viso collo, 7 malformazioni toraciche, 6 anomalie del tratto gastrointestinale, 5 dell’apparato genitourinario e 1 caso di sospetta emivertebra lombare. L’ecografia è stata più accurata della risonanza in 15 casi (3,9%). In 37 casi (9,7%) entrambe le tecniche hanno dato esito diverso rispetto agli accertamenti postnatali. Conclusioni: l’ecografia prenatale rimane a tutt’oggi la principale metodica di imaging fetale. In alcuni casi complessi e/o dubbi sia del sistema nervoso centrale sia degli altri distretti anatomici la risonanza può aggiungere informazioni rilevanti.

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Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

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The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.

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The times following international or civil conflicts but also violent revolutions often come with unequal share of the peace dividend for men and women. Delusions for women who gained freedom of movement and of roles during conflict but had to step back during reconstruction and peace have been recorded in all regions of the world. The emergence of peacebuilding as a modality for the international community to ensure peace and security has slowly incorporated gender sensitivity at the level of legal and policy instruments. Focusing on Rwanda, a country that has obtained significant gender advancement in the years after the genocide while also obtaining to not relapse into conflict, this research explores to what extent the international community has contributed to this transformation. From a review of evaluations, findings are that many of the interventions did not purse gender equality, and overall the majority understood gender and designed actions is a quite superficial way which would hardly account for the significative advancement in combating gender discrimination that the Government, for its inner political will, is conducting. Then, after a critique from a feminist standpoint to the concept of human security, departing from the assumption (sustained by the Governemnt of Rwanda as well) that domestic violence is a variable influencing level of security relevant at the national level, a review of available secondary data on GBV is conducted an trends over the years analysed. The emerging trends signal a steep increase in prevalence of GBV and in domestic violence in particular. Although no conclusive interpretation can be formulated on these data, there are elements suggesting the increase might be due to augmented reporting. The research concludes outlining possible further research pathways to better understand the link in Rwanda between the changing gender norms and the GBV.