Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

Last update: Dec 30, 2022

Overview

Attention Gated Networks
(Image Classification & Segmentation)

Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framework can be utilised in both medical image classification and segmentation tasks.

The schematics of the proposed Attention-Gated Sononet

The schematics of the proposed additive attention gate

References:

"Attention-Gated Networks for Improving Ultrasound Scan Plane Detection", MIDL'18, Amsterdam
Conference Paper
Conference Poster
"Attention U-Net: Learning Where to Look for the Pancreas", MIDL'18, Amsterdam
Conference Paper
Conference Poster

Installation

pip install --process-dependency-links -e .

Owner

Ozan Oktay

Research Scientist @ Microsoft Research Cambridge

GitHub Repository

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Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

Related tags

Overview

Attention Gated Networks
(Image Classification & Segmentation)

References:

Installation

Owner

Ozan Oktay

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Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

Related tags

Overview

Attention Gated Networks (Image Classification & Segmentation)

References:

Installation

Owner

Ozan Oktay

DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

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The project page of paper: Architecture disentanglement for deep neural networks [ICCV 2021, oral]

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Attention Gated Networks
(Image Classification & Segmentation)