Project-MONAI / Project-MONAI/tutorials
MONAI examples to imitate SynthSR and Synthseg in Freesurfer
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- Dominant language
- Jupyter Notebook
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Description
Is your feature request related to a problem? Please describe.
I am looking for a tutorial for superresolution models with MONAI. That is models that can learn the mapping between
(1) low-resolution or low-quality (e.g., clinical scans) and (2) semantic segmentation maps (exact opposite of getting semantic segmentation from T1 scans)
with
high-quality scans.
These two requests have different utilities in practice.
There are prior implementations in Freesurfer but I do not know of any similar tutorial using MONAI.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the SynthSR reference linked in the issue and the requested mapping between low-quality scans, high-quality scans, and semantic segmentation maps. Done would be a MONAI tutorial demonstrating the requested superresolution workflow, but the issue does not identify a target notebook, dataset, tests, or specific entry point.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100