National Brain Mapping Lab

Image processing

Introduction to brain image processing:

The goal of brain image processing is to quantify brain features using brain images and mathematical techniques. Quantification of brain features helps researchers to have a better understanding of the brain functions and structures. This quantitation also assist physician with diagnosis of different disease. For instance, the quantization of brain structural images gives us the opportunity to compare volumes of different brain parts between subjects and image processing laboratory helps researchers through extracting quantitative features from brain images.

 

Introduction to brain image processing
Figure 1. Procedure of medical image acquisition and analysis.

 

 

Introduction to Magnetic Resonance Imaging (MRI):

Magnetic resonance imaging is a technique which use strong magnetic fields and various radio waves to depict pictures of the brain. Using different pulse sequences, it’s possible to record images representing different features of the brain. Structural, functional and diffusion weighted MRI are the most well-known MRI type.

Introduction to functional Magnetic Resonance Imaging (fMRI):

Oxygen is delivered to neurons by hemoglobin. When neural activity increases, the local demand for oxygen increases and correspondingly, the local blood flow increases. Hemoglobin has different characteristics when it is with or without oxygen. When hemoglobin is with oxygen, it has magnetic characteristic. This blood characteristic causes small changes in MR signal. Since the blood oxygen changes depending on the level of neural activity, these changes can be used for brain activity acquisition, this type of MR is known as blood oxygen level dependent(BOLD) or Functional MRI(fMRI).

 

Introduction to functional Magnetic Resonance Imaging (fMRI)
Figure 2. Increase in blood flow in response to neural activity.

 

 

Introduction to Diffusion Weighted Imaging (DWI):

Diffusion-weighted magnetic resonance imaging Is an imaging technique which use the diffusion property of water molecules to produce MR images. In contrast with water molecules in a glass of water which can diffuse to all direction (isotropic diffusion), water molecules diffusion direction in different tissues is different (anisotropic diffusion).

The measured anisotropic diffusion shows inhomogeneity in microscopic tissues. In white matter of the brain, anisotropic diffusion is due to cell membrane (myelin membrane) and axon bundles. Anisotropic diffusion can show tissue direction. In white matter, diffusion direction shows fiber directions.

 

Introduction to Diffusion Weighted Imaging (DWI)
Figure 3. Fast diffusion of water molecules through the axon direction and slow diffusion of water molecules through a perpendicular direction to the axon.

 

 

Introduction to fMRI image processing:

There are two type of fMRI studies, the first one which is called task fMRI, tries to record brain activity during a specific task. This kind of study is usually performed under a specific cognitive task and the goal is to find brain regions that are associated with that specific cognitive task. The other kind of fMRI study, investigates brain activity during the rest, this kind of study is called rest fMRI. There are two main image processing method for analysis of fMRI images, data driven and model base methods.

 

Introduction to fMRI image processing
Figure 4. Sample analyzed fMRI data. Active regions are highlighted with yellow and orange colors.

 

 

Introduction to DWI image processing:

As previously stated, direction of water molecules diffusion in white matter of the brain shows the direction of fiber bundles in brain. Therefore, in DWI image processing we investigate water molecules directions. The most common image processing technique for DWI images processing is DTI. In DWI image processing using DTI technique, a model called tensor is fitted to the data. Next, using the calculated tensor, parameter such as fractional anisotropy(FA), the main diffusion direction, mean diffusion can be calculated.

 

Introduction to DWI image processing
Figure 5. Sample FA map obtained analyzing diffusion weighted images.

 

 

list of services offered by NBML image processing laboratory:

fMRI image processing:

  • Preprocessing of fMRI data
  • Processing of rest-fMRI data using ICA method
  • Processing of task-fMRI data using GLM method

DWI image processing:

  • Quality Control (QC) of DWI images
  • Preprocessing of DWI images
  • Tensor fitting to DWI images

The brain image processing laboratory in NBML is one of the first centers that provide brain image processing services for researchers in Iran. In this lab, processing a wide range of MR images including structural, functional and diffusion weighted images is accomplish using variety of specialized softwares. Also, we offer consultancy services and advisors in this lab would be happy to answer researcher’s brain image processing questions.

Source of Neuroimaging Tools:

Neuroimaging tools Web Link Platform
3D slicer http://www.slicer.org/ Windows, Linux, Mac
AFNI http://afni.nimh.nih.gov/afni/ Unix
BrainVoyager https://www.pstnet.com/software.cfm?ID=97 Windows, Linux, Mac OS X
CAMINO http://cmic.cs.ucl.ac.uk/camino/ Java
Explore DTI http://www.ExploreDTI.com Windows, Unix, Mac
FreeSurfer http://www.freesurfer.net/ Linux, Mac OS X, Windows
FSL http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/ Linux, Mac OS X, Windows
MRIcro http://www.mricro.com/ Windows, Linux, Mac
MRtrix http://www.brain.org.au/software/ Windows, Unix, Linux,Mac OS X
SPM http://www.fl.ion.ucl.ac.uk/spm/ N/A
Work Bench http://www.humanconnectome.org/software/get-connectome-workbench Linux, Mac OS X, Windows

A Review on the Bioinformatics Tools for Neuroimaging, Man et al, Special Issue Neuroscience 2015


In NBML’s image processing lab, open source programs are only used for research and scientific purposes and there will be no commercial use.