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ai-med / quickNAT_pytorch

PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

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Re-train the model with new data: 3 view aggregation

rockNroll87q opened this issue · comments

commented

Dear authors,

First of all, great work and thanks for the code!
I'm trying to re-train the model with my data and it seems to run.

I only have a question. It seems possible to select the orientation (COR, AXI, SAG), but how I create a model that aggregate all of these 3?

Thanks!

commented

Hi,

Details for training and deploying with View Aggregation is added in the recent commits. I omitted the SAG axis and only used AXI and COR for now to optimize between performance and deployment time.

Best
Abhijit