Summary and Schedule

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00h 00m

1. A Practical Introduction to Working with Medical Image Data

How can we visualize volumetric data?
How do locations in an image get mapped to real-world coordinates?
How can we register different types of images together using ITK-SNAP?

00h 12m

2. Demons Image Registration

How to understand and visualise three image in one pane for demons image registration algorithm?

00h 24m

Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

Github setup

You might have already a GitHub, otherwise please create one
Generate your SSH keys as suggested here
Clone the repository by typing (or copying) the following lines in a terminal

git clone git@github.com:HealthBioscienceIDEAS/Medical-Image-Registration-Short-Course.git

Dataset

Download the data zip file and unzip it to your Desktop

CT-vs-PET-Ventilation-Imaging

CT Ventilation as a Functional Imaging Modality for Lung Cancer Radiotherapy from TCIA. We recommend to focus on exhale/inhale breath hold CT (BHCT) Dicoms. Bare in mind that: * The BHCT scans for CT-PET-VI-02 & CT-PET-VI-03 show very little motion between inhale and exhale * The BHCT scans for CT-PET-VI-05 have a different number of slices between the inhale and exhale

Extracting and renaming data paths

Original data directory paths for this work were renamed for easy interpretability as follows:
* 5.000000-Thorax Insp 2.0 B* renamed as inhale_BH_CT
* 7.000000-Thorax Exp 2.0 B* renamed as exhale_BH_CT
* 3.000000-CT Lung 3.0 B* renamed as CT_for_PET
* 4.000000-Galligas Lung-0* renamed as PET

See how the original data paths and renamed paths look like

BASH

#Original directory paths
/CT-PET-VI-02$ tree -d 
.
├── 1000.000000-PET SUV Factors-26496 [1 item, with size 42.1 kB]
├── 3.000000-CT Lung  3.0  B31f-61322  [175 items, totalling 92.4 MB]
├── 4.000000-Galligas Lung-03537 [159 items, totalling 51.5 MB]
├── 5.000000-Thorax Insp  2.0  B70f-29873 [167 items, totalling 88.1 MB]
├── 7.000000-Thorax Exp  2.0  B70f-73355 [167 items, totalling 88.1 MB]
└── 8.000000-RespLow  2.0  B30s  80  Ex - 100  In-44317 [810 items, totalling 426.9 MB]
#Renamed directory paths
.
├── CT-PET-VI-02
│   ├── CT_for_PET
│   ├── exhale_BH_CT
│   ├── inhale_BH_CT
│   └── PET




#Original directory paths
/CT-PET-VI-03$ tree -d
.
├── 06-25-1996-RTRTRespLowBreathRateRNS Adult-43080
│   ├── 1000.000000-PET SUV Factors-06580
│   ├── 3.000000-CT Lung  3.0  B31f-08354
│   └── 4.000000-Galligas Lung-15379
└── 06-25-1996-RTRTRespLowBreathRateRNS Adult-87093
    ├── 5.000000-Thorax Insp  2.0  B70f-42000
    ├── 7.000000-Thorax Exp  2.0  B70f-45310
    └── 8.000000-RespLow  2.0  B30s  80  Ex - 100  In-54790
#Renamed directory paths for `06-25-1996-RTRTRespLowBreathRateRNS Adult-43080`
├── CT-PET-VI-03
│   ├── CT_for_PET
│   └── PET





#Original directory paths
/CT-PET-VI-05$ tree -d
└── 12-10-1996-RTRTRespLowBreathRateRNS Adult-37585
    ├── 1000.000000-PET SUV Factors-63910
    ├── 3.000000-CT Lung  3.0  B31f-90638
    ├── 4.000000-Galligas Lung-26361
    ├── 5.000000-Thorax Insp  2.0  B70f-45546
    ├── 7.000000-Thorax Exp  2.0  B70f-31579
    └── 8.000000-RespLow  2.0  B30s  80  Ex - 100  In-16454
#Renamed directory paths
├── CT-PET-VI-05
│   ├── CT_for_PET
│   ├── exhale_BH_CT
│   ├── inhale_BH_CT
│   └── PET





#Original directory paths
/CT-PET-VI-07$ tree -d
.
└── 02-14-1997-RTRTRespLowBreathRateRNS Adult-80512
    ├── 1000.000000-PET SUV Factors-99730
    ├── 4.000000-Galligas Lung-82849
    ├── 5.000000-Thorax Insp  2.0  B70f-20440
    ├── 7.000000-Thorax Exp  2.0  B70f-03567
    └── 8.000000-RespLow  2.0  B30s  80  Ex - 100  In-01782
#Renamed directory paths
└── CT-PET-VI-07
    ├── exhale_BH_CT
    ├── inhale_BH_CT
    └── PET

Software Setup

Installing Dependencies in Python Virtual environments

Installing python virtual environment with dependencies (e.g., nibabel, etc). See further instructions here.

Using conda

BASH

conda create -n "mirVE" python=3.11 pip -c conda-forge
conda config --set pip_interop_enabled True
conda activate mirVE
cd ~/_dependencies
pip install -r requirements.txt

Using python virtual environment

BASH

# Installing dependencies in Ubuntu 22.04
sudo apt-get install -y python3-pip
sudo apt-get install -y python3-venv
# Create path for venv
cd $HOME
mkdir mirVE
cd mirVE
# Create virtual environment
python3 -m venv mirVE
source mirVE/bin/activate
cd ~/_dependencies
python3 -m pip install -r requirements.txt

ITK-Snap

Hardware Requirements

Memory: “Overall 2Gb of memory should be enough for most users; 4Gb should suffice for users with large images.” 🔗
Multi - Operating System:
- ITK-SNAP binaries are distributed for Linux (32 and 64 bit)),
- Windows (64 bit),
- and MacOS Leopard (64 bit).

Installation

Installing ITK-SNAP in differen operating systems

Windows

Open the following link: https://sourceforge.net/projects/itk-snap/files/itk-snap/4.2.0/
Download itksnap-4.2.0-20240422-win64-AMD64.exe
Install it by following default settings.

Linux (tested on Ubuntu 22.04 x64 GNU/Linux)

Open your Terminal to install it

BASH

sudo apt-get install tree # to visualise files and paths
FILENAME=itksnap-nightly-rel_4.0-Linux-gcc64.tar.gz  #Length: 200943059 (192M) [application/x-gzip]
cd ~/Downloads/
mkdir -p itksnap && cd itksnap
wget https://sourceforge.net/projects/itk-snap/files/itk-snap/Nightly/$FILENAME/download -O $FILENAME
tar -xvzf $FILENAME

MacOS

Open the following link: https://sourceforge.net/projects/itk-snap/files/itk-snap/4.2.0/ and download itksnap-4.2.0-20240422-Darwin-x86_64.dmg
Double click the icon for the file you downloaded (e.g., itksnap-3.2.0-rc2-20140919-MacOS-x86_64.dmg).
Drag the icon ITK-SNAP.app to the Applications folder.
Drag the icon itksnap on top of the icon usr_local_bin in that folder.
To add the ITK-SNAP launcher to your Dock, open the Applications folder and drag the ITK-SNAP.app icon onto the dock.