Attention gates that teach CNNs where to look

What it does This repository provides a PyTorch implementation of attention gates for U-Net and VGG-16. The authors propose the framework for medical image classification and segmentation, with published applications in ultrasound scan plane detection and pancreas localization.

The interesting bit The project applies the same attention-gating idea to two distinct architectures: U-Net and VGG-16. The README roots the work in two MIDL 2018 papers, so the scope is tightly bound to those proven medical use cases rather than a generic drop-in layer.

Key highlights

• PyTorch implementation of attention gates for U-Net and VGG-16.
• Framed for medical image classification and segmentation tasks.
• Rooted in two MIDL 2018 papers: ultrasound scan plane detection and pancreas segmentation.
• Includes schematics for the Attention-Gated Sononet and the additive attention gate mechanism.

Caveats

• The README offers only architecture diagrams and paper links; there are no usage examples, dependency details, or code documentation.
• It is unclear whether the implementation extends beyond the two specific medical tasks and backbones described in the references.

Verdict A useful reference if you need a PyTorch take on attention gating for medical imaging. Less helpful if you want a general-purpose, well-documented attention library.