Hippocampal Volume Quantification in Alzheimer's Progression

Project Summary

You have worked with 3D Medical images to curate a dataset of brain MRIs, trained a segmentation on a convolutional neural network, and integrated all of this into a clinical network to quantify hippocampal volume for Alzheimer's progression detection or monitoring.

Submission Checklist

Before you submit, check if the following have been completed:
Note: The checklist above won't save your checkmarks so do this right before you plan to submit.

	Everything in the Rubric is complete.
	The following are in Section 1's /section1/out/ folder/directory.
	Curated dataset with labels, as collection of NIFTI files.
	A Python Notebook or Python File with the results of your Exploratory Data Analysis.
	The following are in Section 2's /section2/out/ folder/directory.
	Functional code that trains the segmentation model.
	Test report with Dice scores on test set (can be json file).
	Screenshots from your Tensorboard (or other visualization engine) output.
	Your trained model PyTorch parameter file (model.pth)
	The following are in Section 3's /section3/out/ folder/directory.
	Code that runs inference on a DICOM volume and produces a DICOM report.
	A report.dcm file with a sample report.
	Screenshots of your report shown in the OHIF viewer.
	1-2 page Validation Plan.

Ready to Submit?

Once you have all the items above completed, you can click the submit button. Follow the directions to submit your project in one of the following ways:

• Submit a zip file
• Submit a Github repo

Note: If you used the Workspace/Online option, you can download the folder or use your Github as a submission.