Hugo Alexandre Ferreira

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The Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox is a fully automated all-in-one connectivity analysis toolbox that offers both pre-processing, connec-tivity, and graph theory analysis of multimodal images such as anatomical, diffusion, and functional MRI, and PET [1]. In this work, the MIBCA functionalities were used to study Alzheimer's(More)
PURPOSE We aimed to compare two different methods of region of interest (ROI) demarcation and determine interobserver variability on apparent diffusion coefficient (ADC) in breast lesions. METHODS Thirty-two patients with 39 lesions were evaluated with a 3.0 Tesla scanner using a diffusion-weighted sequence with several b-values. Two observers(More)
  • Tânia Faria Vaz, Filipa Lucena, Joana Pé-Leve, André Santos Ribeiro, Luís Lacerda, Nuno da Silva +3 others
  • 2015
Alzheimer Disease (AD) is characterized by progressive cognitive decline and dementia. Earlier diagnosis and classification of different stages of the disease are currently the main challenges and can be assessed by neuroimaging. With this work we aim to evaluate the quality of brain regions and neuroimaging metrics as biomarkers of AD. Multimodal Imaging(More)
Rehabilitation after stroke is of crucial importance since patients often have severe motor impairments that affect their daily activities. In the past decades, a number of robotic systems have been proposed for stroke rehabilitation but very few of them are available in the market. Additionally, because of their high costs they are not widely accessible.(More)
Brain activity results from anatomical and functional connections that can be disrupted or altered due to trauma or lesion. This work presents a first approach on the study of whole-brain connectivity of brain tumor patients using the Multimodal Imaging Brain Connectivity (MIBCA) toolbox. Two patients with glioblastoma lesions located in the left hemisphere(More)
Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single(More)
Electroencephalography (EEG) signals' interpretation is based on waveform analysis, where meaningful information should emerge from a plethora of data. Nonetheless, the continuous increase in computational power and the development of new data processing algorithms in the recent years have put into reach the possibility of analyzing raw EEG signals. Bearing(More)
Neurological disorders, in particular Stroke, have a substantial impact on a great number of individuals worldwide. These individuals are often left with residual motor control in their upper limbs. Although conventional therapy can aid in restoring some of the lost movement, it is not always accessible, and the procedures are dull and unappealing for the(More)