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Update README with project results and outputs
Added results and outputs section detailing model fine-tuning and 3D Slicer integration.
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PW45_2026_Boston/Projects/FineTuningSimcortexUsingManuallyCorrectedCorticalAnnotations/README.md

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@@ -69,6 +69,28 @@ A second illustration shows the local SimCortex 3D Slicer extension with reconst
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<img width="2048" height="1351" alt="Image" src="https://github.com/user-attachments/assets/81cdc66f-5362-41cf-af7f-2385b1023b8d" />
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## Results and Outputs from Project Week
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During Project Week, we worked on two main directions: model fine-tuning and 3D Slicer integration.
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For the fine-tuning part, we trained SimCortex using 30 manually corrected segmentations and cortical
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surfaces. We tested different training configurations and evaluated the models on three independent
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datasets (CNP, ds001486, HCP/OASIS), covering 120 test subjects in total. The evaluation includes
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surface distance metrics (Chamfer, ASSD, HD90), self-intersection fraction (SIF), cortical thickness
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error, and inter-surface collision checks.
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The tables below summarize the quantitative comparison between the baseline SimCortex and
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SimCortex FineTune.
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<!-- Replace the src below with your actual uploaded image URLs -->
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<img width="1142" height="315" alt="image" src="https://github.com/user-attachments/assets/a06a9fa2-5271-41ff-b143-f9e94fb3d086" />
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<img width="1091" height="278" alt="image" src="https://github.com/user-attachments/assets/ba70bdfd-bc82-45f4-8a58-286bd5e4c9b7" />
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For the 3D Slicer part, the SimCortex extension was merged into the official 3D Slicer Extensions
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Index. Users can now install it directly from Slicer, run the full pipeline from a T1-weighted MRI
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through Docker, and load the reconstructed white and pial surfaces back into Slicer for visualization.
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# Background and References
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* SimCortex GitHub repository:

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