Hi everyone,
I’m currently working on a medical imaging project that involves aligning a series of 3D MRI scans with a reference image for longitudinal analysis. I’ve been exploring ITK as the primary library to handle the registration, but I’m relatively new to its framework and could use some guidance on best practices and pipeline structuring.
The specific goal is to perform deformable registration between the baseline and follow-up scans, and I’d like to include a preprocessing step for bias field correction and intensity normalization. I’m aware that ITK provides tools for each of these, but integrating them into a clean and modular pipeline is proving to be challenging.
Some questions I have:
- What’s the recommended way to structure a registration pipeline in ITK when combining preprocessing, rigid, and deformable steps?
- Are there particular filters or components you’d suggest for robust bias correction and intensity normalization before registration?
- Would it be better to rely solely on ITK or integrate SimpleITK for any parts of the pipeline, especially for visualization and debugging?
- Are there any open-source examples or templates that demonstrate a full multi-step registration workflow?
I’d appreciate any insights, suggestions, or sample code for sap abap training in bangalore you can share. Also, if anyone has encountered pitfalls or performance considerations when working with large 3D datasets in ITK, I’d love to hear about your experience.
Thanks in advance for your time and help!