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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)
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)
Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the(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)
Epilepsy is one of the most important chronic neurological disorders worldwide affecting more than 50 million people of all ages. Among these, almost 20% of epilepsy cases are uncontrollable and have an unknown source of this abnormal electrical activity. Present techniques for the detection of epileptogenic foci include electroencephalo-graphy (EEG),(More)
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)
Forschungszentrum Jülich GmbH, Jülich, Germany Attenuation correction of PET data acquired in hybrid MR/PET scanners is still a challenge. Different methods have been adopted by several groups to obtain reliable attenuation maps (mu-maps). In this study we compare three methods: MGH, UCL, Neural-Network. The MGH method is based on an MR/CT template obtained(More)
A system structure, i.e., how elements of a system are connected, is a key factor for information retention and transmission through its elements. From the system dynamics, i.e., the states of the elements over time, we measure the system's ability to propagate information through its elements as the pairwise mutual information (pMI) between the elements at(More)
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