Once you finish processing your data through iBEAT, you will have a labeled brain that has a file name ending in "reoriented-strip-seg-aal.img" This file contains 90 regions from the AAL atlas. I have brought this file into FSL to calculate volume of each labeled region. First, you will need to use mri_convert or fslchfiletype to … Continue reading Using iBEAT output to measure regional volume

Once you have successfully segmented the tissue into gray matter, white matter, and CSF, you can use the atlases in iBEAT to label the cortical and subcortical regions of the brain. Open the "Brain Labeling" step from the tissue segmentation step or from the main iBEAT window and load in the tissue segmented data. Click … Continue reading iBEAT Step 4: Brain Labeling

Tissue segmentation - separating gray matter and white matter - is the step where I have run into the most errors. One thing that is clear is that the age of the subject matters for tissue segmentation. When I have incorrectly entered the age of subjects, I have ended up with errors during this step. … Continue reading iBEAT Step 3: Tissue Segmentation

The next step in iBEAT is brain extraction. If you are moving on from the image preprocessing step, you can open the brain extraction step directly from the image preprocessing window, and it will open with your subject images loaded. If you closed the image preprocessing window already, click the brain extraction button in the … Continue reading iBEAT Step 2: Brain Extraction

The first step to process your infant MRI data using iBEAT is to perform image preprocessing. This step includes 1) reorientation and resampling and 2) N3 correction. To start the image preprocessing, click the Image Preprocessing button in the box that popped up when you typed “ibeat” into the terminal. Then, load in your subject … Continue reading iBEAT Step 1: Image Preprocessing

Loading your subject images is easiest if your data is prepared using the recommended file names and directory structure. When you click the button at the top left that says “Load Subject Images,” a window will pop up. The window has three drop-down boxes at the top. The first drop-down box allows you to select … Continue reading iBEAT: Loading Subject Images

The current version of iBEAT (version 1.1) only works on Linux. Future versions are expected to be compatible with Windows and Mac. For now, I will walk you through how to run iBEAT on a Linux machine. You can use iBEAT in a terminal running either bash or csh. From what I can tell, there … Continue reading Starting iBEAT

If you want to use iBEAT in the user-friendly way it was designed, it is best to use their directory structure to organize your data. Within your data folder, you will have a folder for each subject. These folders will be named with the subject ID (e.g., S0001). Within each subject folder, you should create … Continue reading Preparing your data for iBEAT