Human brain mapping fsl course
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For these reasons, the pipeline proposed in this work consists in an implementation of already described algorithms combined according to a hierarchical order in a semi-automated manner.
HUMAN BRAIN MAPPING FSL COURSE SOFTWARE
This approach should be based on the activation of the different software modules according to a logical sequence leading to precise measurements of DWI and PWI values in focal MS lesions, in normal appearing grey matter (NAGM) and in normal appearing white matter (NAWM). Thus, a more integrated analysis process incorporating all software packages employed in performing co-registration and tissue/lesion segmentation steps would be beneficial. In addition, there are no large-scale studies investigating DWI and PWI abnormalities in MS focal lesions categorized according to different stages of their evolution (acute and chronic). These limitations could explain why the results coming from previous studies were not always concordant.
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This implies several steps including various co-registration and tissue/lesion segmentation tasks which make the analysis rather laborious, time-consuming and prone to inaccuracies due to human intervention. However, the evaluation of DWI and PWI alterations in MS is generally restricted to the research field and is currently performed by different software programs, used separately from each other with lack of standardization regarding the overall process. Therefore, further studies are warranted to clarify the actual significance of DWI and PWI disturbances in MS. As DWI and PWI can be easily integrated in the context of MRI examination, this may have a large impact for routine clinical setting and patient quality of life. Thus, it could be crucial to understand whether the detection and quantification of focal and diffuse DWI and PWI changes may help in recognizing the different mechanisms implicated in MS damage and, as a consequence, in improving diagnostic accuracy, early outcome prediction and response to treatment monitoring in MS. In fact, although conventional MRI findings are currently considered a valid surrogate marker for MS diagnosis and progression in treated and untreated patients, their diagnostic and prognostic value still remains very limited given the inability of conventional MRI in identifying the specific pathologic substrates of MS lesions. The role of diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) modalities in multiple sclerosis (MS) has recently received increased attention due to the potential of these two advanced magnetic resonance imaging (MRI) techniques in detecting the structural and hemodynamic characteristics of MS-related focal and diffuse brain abnormalities in gray and white matter, which characterize the well-known heterogeneity of the disease. All these steps are automatic, except for lesion segmentation and classification.
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We generated the Diffusion/Perfusion Project (DPP) Suite, in which a series of external software programs are managed and harmonically and hierarchically incorporated by in-house developed Matlab software to perform the following processes: 1) image pre-processing, including imaging data anonymization and conversion from DICOM to Nifti format 2) co-registration of 2D and 3D non-enhanced and Gd-enhanced T1-weighted images in fluid-attenuated inversion recovery (FLAIR) space 3) lesion segmentation and classification, in which FLAIR lesions are at first segmented and then categorized according to their presumed evolution 4) co-registration of segmented FLAIR lesion in T1 space to obtain the FLAIR lesion mask in the T1 space 5) normal appearing tissue segmentation, in which T1 lesion mask is used to segment basal ganglia/thalami, normal appearing grey matter (NAGM) and normal appearing white matter (NAWM) 6) DWI and PWI map generation 7) co-registration of basal ganglia/thalami, NAGM, NAWM, DWI and PWI maps in previously segmented FLAIR space 8) data analysis.