This thesis presents a 3D semi-automatic segmentation technique for extracting the lumen surface of the Carotid arteries including the bifurcation from 3D and 4D ultrasound examinations. Ultrasound images are inherently noisy. Therefore, to aid the inspection of the acquired data an adaptive edge preserving filtering technique is used to reduce the general high noise level. The segmentation process starts with edge detection with a recursive and separable 3D Monga-Deriche-Canny operator. To reduce the computation time needed for the segmentation process, a seeded region growing technique is used to make an initial model of the artery. The final segmentation is based on the inflatable balloon model, which deforms the initial model to fit the ultrasound data. The balloon model is implemented with the finite element method. The segmentation technique produces 3D models that are intended as pre-planning tools for surgeons. The results from a healthy person are satisfactory and the results from a patient with stenosis seem rather promising. A novel 4D model of wall motion of the Carotid vessels has also been obtained. From this model, 3D compliance measures can easily be obtained.

<p>This thesis presents a 3D semi-automatic segmentation technique for extracting the lumen surface of the Carotid arteries including the bifurcation from 3D and 4D ultrasound examinations. </p><p>Ultrasound images are inherently noisy. Therefore, to aid the inspection of the acquired data an adaptive edge preserving filtering technique is used to reduce the general high noise level. The segmentation process starts with edge detection with a recursive and separable 3D Monga-Deriche-Canny operator. To reduce the computation time needed for the segmentation process, a seeded region growing technique is used to make an initial model of the artery. The final segmentation is based on the inflatable balloon model, which deforms the initial model to fit the ultrasound data. The balloon model is implemented with the finite element method. </p><p>The segmentation technique produces 3D models that are intended as pre-planning tools for surgeons. The results from a healthy person are satisfactory and the results from a patient with stenosis seem rather promising. A novel 4D model of wall motion of the Carotid vessels has also been obtained. From this model, 3D compliance measures can easily be obtained.</p>

A inferência do curso temporal da atividade neural a partir do efeito BOLD é um importante problema, ainda em aberto. A forma da curva BOLD não reflete diretamente as características temporais da atividade eletrofisiológica dos neurônios. Nessa tese, é introduzido o conceito de tempo de processamento neural (TPN) como um dos parâmetros do modelo biofísico da função de resposta hemodinâmica (HRF). O objetivo da introdução desse conceito é obter estimativas mais acuradas da duração da atividade neural a partir do efeito BOLD, que possui auto grau de nãolinearidade. Duas formas de estimar os parâmetros do modelo do efeito BOLD foram desenvolvidas. A validade e aplicabilidade do conceito de TPN e das rotinas de estimação foram avaliadas por simulações computacionais e análise de séries temporais experimentais. Os resultados das simulações e da aplicação foram comparados com medidas da forma da HRF. O experimento analisado consistiu em um paradigma de tomada de decisão na presença de distratores emocionais. Esperase que o TPN em áreas sensoriais primárias seja equivalente ao tempo de apresentação de estímulos. Por outro lado, o TPN em áreas relacionadas com a tomada de decisão deve ser menor que a duração dos estímulos. Além disso, o TPN deve depender da condição experimental em áreas relacionadas ao controle de distratores emocionais. Como predito, o valores estimados do TPN no giro fusiforme foram equivalentes à duração dos estímulos e o TPN no giro do cíngulo dorsal variou com a presença de distrator emocional. Observou-se ainda lateralidade do TPN no córtex pré-frontal dorsolateral. As medidas da forma da HRF obtidas por um método convencional não dectectaram as variações observadas no TPN / The extraction of information about neural activity dynamics related to the BOLD signal is a challenging task. The temporal evolution of the BOLD signal does not directly reflect the temporal characteristics of electrical activity of neurons. In this work, we introduce the concept of neural processing time (NPT) as a parameter of the biophysical model of the hemodynamic response function (HRF). Through this new concept we aim to infer more accurately the duration of neuronal response from the highly nonlinear BOLD effect. We describe two routines to estimate the parameters of the HRF model. The face validity and applicability of the concept of NPT and the estimation procedures are evaluated through simulations and analysis of experimental time series. The results of both simulation and application were compared with summary measures of HRF shape. We analysed an experiment based on a decision-making paradigm with simultaneous emotional distracters. We hypothesize that the NPT in primary sensory areas is approximately the stimulus presentation duration. On the other hand, the NPT in brain areas related to decisionmaking processes should be less than the stimulus duration. Moreover, in areas related to processing of an emotional distracter, the NPT should depend on the experimental condition. As predicted, the NPT in fusiform gyrus is close to the stimulus duration and the NPT in dorsal anterior cingulate gyrus depends on the presence of an emotional distracter. Interestingly, the estimated NPTs in the dorsolateral prefrontal cortex indicate functional laterality of this region. The analysis using standard measures of HRF did not detect the variations observed in our method (NPT)

A inferência do curso temporal da atividade neural a partir do efeito BOLD é um importante problema, ainda em aberto. A forma da curva BOLD não reflete diretamente as características temporais da atividade eletrofisiológica dos neurônios. Nessa tese, é introduzido o conceito de tempo de processamento neural (TPN) como um dos parâmetros do modelo biofísico da função de resposta hemodinâmica (HRF). O objetivo da introdução desse conceito é obter estimativas mais acuradas da duração da atividade neural a partir do efeito BOLD, que possui auto grau de nãolinearidade. Duas formas de estimar os parâmetros do modelo do efeito BOLD foram desenvolvidas. A validade e aplicabilidade do conceito de TPN e das rotinas de estimação foram avaliadas por simulações computacionais e análise de séries temporais experimentais. Os resultados das simulações e da aplicação foram comparados com medidas da forma da HRF. O experimento analisado consistiu em um paradigma de tomada de decisão na presença de distratores emocionais. Esperase que o TPN em áreas sensoriais primárias seja equivalente ao tempo de apresentação de estímulos. Por outro lado, o TPN em áreas relacionadas com a tomada de decisão deve ser menor que a duração dos estímulos. Além disso, o TPN deve depender da condição experimental em áreas relacionadas ao controle de distratores emocionais. Como predito, o valores estimados do TPN no giro fusiforme foram equivalentes à duração dos estímulos e o TPN no giro do cíngulo dorsal variou com a presença de distrator emocional. Observou-se ainda lateralidade do TPN no córtex pré-frontal dorsolateral. As medidas da forma da HRF obtidas por um método convencional não dectectaram as variações observadas no TPN / The extraction of information about neural activity dynamics related to the BOLD signal is a challenging task. The temporal evolution of the BOLD signal does not directly reflect the temporal characteristics of electrical activity of neurons. In this work, we introduce the concept of neural processing time (NPT) as a parameter of the biophysical model of the hemodynamic response function (HRF). Through this new concept we aim to infer more accurately the duration of neuronal response from the highly nonlinear BOLD effect. We describe two routines to estimate the parameters of the HRF model. The face validity and applicability of the concept of NPT and the estimation procedures are evaluated through simulations and analysis of experimental time series. The results of both simulation and application were compared with summary measures of HRF shape. We analysed an experiment based on a decision-making paradigm with simultaneous emotional distracters. We hypothesize that the NPT in primary sensory areas is approximately the stimulus presentation duration. On the other hand, the NPT in brain areas related to decisionmaking processes should be less than the stimulus duration. Moreover, in areas related to processing of an emotional distracter, the NPT should depend on the experimental condition. As predicted, the NPT in fusiform gyrus is close to the stimulus duration and the NPT in dorsal anterior cingulate gyrus depends on the presence of an emotional distracter. Interestingly, the estimated NPTs in the dorsolateral prefrontal cortex indicate functional laterality of this region. The analysis using standard measures of HRF did not detect the variations observed in our method (NPT)