Attention U-Net for OASIS Brain Tissue Segmentation

[ywbrian]

An Attention U-Net model that performs semantic segmentations of brain MRI scans from the OASIS dataset.

[wangzhaomxy]

<This is an initial inspection, no action is required at this point.>

File Organizing:
There is only a single Python script combining all functions, which does not meet the required instructions.

Problem Solving:

• The algorithm appears to solve the problem correctly. However, the report contains no testing results, and there are no training, validation, or testing outcomes presented to demonstrate that the project has been fully completed.
• Accuracy in testing dataset (Dice): NO test results in the report.

Model and functions:

• It correctly uses PyTorch to construct the improved UNet 2D models and functions.
• NO data augmentation.
• Properly use the train/validation/test datasets.

Code design: Functional works.

Code comment and docstring:

• Good code comments
• Good function docstrings
• NO header block

Difficulty: Easy.

Additional Comments:

• Minimal commits, consisting mostly of generic messages such as ‘update’ or ‘add function.’ More meaningful and descriptive commit messages are expected.
• The extremely minimal report, lacking any supporting evidence, indicates that the project is unfinished.

[wangzhaomxy]

Hi there, Please provide your student number or full name; otherwise, we won’t be able to allocate your marks.

[gayanku]

Marking

Good/OK/Fair Practice (Design/Commenting, TF/Torch Usage)
	No design and implementation.	-2
	Spacing and comments.
	No Header blocks.	-1
Recognition Problem
	OK solution to problem.	-2
	Driver Script present.
	File structure NOT present.	-1
	Good Usage & Demo & Visualisation & Data usage.
	Module present.
	Commenting present.
	No Data leakage found.
	Difficulty : Easy. Easy. ImprovedUnet2D	-10
Commit Log
	Good Meaningful commit messages.
	Good Progressive commits. 1 day.	-2
Documentation
	Readme :Acceptable.	-2
	Model/technical explanation :Acceptable.	-2
	Description and Comments :Good.
	Markdown used and PDF submitted.
Pull Request
	Successful Pull Request (Working Algorithm Delivered on Time in Correct Branch).
	No Feedback required.
	Request Description is missing.	-2
TOTAL		-24

Marked as per the due date and changes after which aren't necessarily allowed to contribute to grade for fairness.
Subject to approval from Shakes

[ywbrian]

Hi there, Please provide your student number or full name; otherwise, we won’t be able to allocate your marks.

Check the bottom of the README