We have implemented a number of pipelines as part of our NeCTAR RT035 project. Brief descriptions of the pipelines implemented are described below.
The SUVR tool provides intensity normalisation of PET images for quantitative purposes.
The Registration tool allows the user to perform affine or rigid transforms when registering two images together.
The segmentation tool allows the user to segment a brain for a given MRI image.
Alzheimer’s disease and other neuro degenerative diseases are associated with the loss of Grey matter in the cortex. It is therefore necessary to try and quantify this loss. We use the cortical thickness estimation (CTE) tool to provide us with this analysis.
Overview of main functions of CTE implemented:
- Atlas registration
- Align an atlas image to a target image
- Segment the MRI into Grey matter (GM), white matter (WM) and cerebrospinal fluid
- Bias Field Correction
- Estimate and remove the noise from the image
- Partial Volume Estimation
- Quantify the amount of partial voluming inside each voxel
- Topology Correction
- Create the topology of the brain to ensure that it is genus zero
- Thickness Estimation
- Compute the thickness of the cortex for each grey matter voxel
Overview of main functions implemented for CTE Surface:
- Cortical Surface Extraction
- Extract a 3D mesh from the brain segmentation
- Topological Correction
- Removes holes and handles from the mesh
- Biomarker mapping on cortical surface
- Mapping of various values on a mesh i.e. Thickness, PET values, MR Intensity
- Surface registration
- Align the meshes of any given subject to a template to obtain a correspondence across subjects
- Transfer of biomarkers on template surface
- Map all values from all subjects to a common space where they
- Can be compared
Galaxy allows us to create a workflow by joining two or more pipelines together. We use workflows to connect the CTE with CTE surface pipelines as shown in the picture:
|Galaxy based workflows for CTE|
Overview of main functions implemented for PET PVC:
- PVC registration
- Registration of the PET Image to its corresponding MRI
- Segmentation of the MRI into GM, WM and CSF
- Partial Volume Correction (PVC)
- Correction for spill in and spill over of the PET image using the MRI segmentation