Project: SlicerModalityConverter Extension - addition of new models and use case examples #1574
Description
Draft Status
Ready - team will start page creating immediately
Category
Quantification and Computation
Key Investigators
- Ciro Benito Raggio (Karlsruhe Institute of Technology, Germany)
- Paolo Zaffino (Magna Graecia University of Catanzaro, Italy)
- Maria Francesca Spadea (Karlsruhe Institute of Technology, Germany)
Project Description
SlicerModalityConverter is a 3D Slicer extension designed for medical image-to-image (I2I) translation.
The ModalityConverter module provides a user-friendly interface for integrating multiple AI models trained for I2I translation (currently MRI-to-CT). It also supports GPU acceleration for faster inference, and is designed to allow users to easily integrate custom models.
More about the module here: https://github.com/ciroraggio/SlicerModalityConverter
Objective
- Integration of new translation models for T1w-to-T2w MRI translation.
- Creating use case examples with video tutorials.
Approach and Plan
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Integrate two new pre-trained models for T1w-to-T2w translation (presented in this study and released in this repository), following the guidelines reported in the module documentation for integrating custom models.
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Create video tutorials demonstrating the common uses of existing models. For example, show how to use MRI-to-synthetic CT translation models to extract the skull's representation from a T1w brain MRI.
Progress and Next Steps
- Describe specific steps you have actually done.
Illustrations
No response
Background and References
No response