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Found 6 papers, 2 papers with code
Automatic Generation of Synthetic Colonoscopy Videos for Domain Randomization
An increasing number of colonoscopic guidance and assistance systems rely on machine learning algorithms which require a large amount of high-quality training data.
Multi-Contrast Computed Tomography Healthy Kidney Atlas
However, there is no abdominal and retroperitoneal organs atlas framework for multi-contrast CT.
Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking
While deep learning has achieved significant advances in accuracy for medical image segmentation, its benefits for deformable image registration have so far remained limited to reduced computation times.
Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images
AGs can be easily integrated into standard CNN models such as VGG or U-Net architectures with minimal computational overhead while increasing the model sensitivity and prediction accuracy.
Attention U-Net: Learning Where to Look for the Pancreas
We propose a novel attention gate (AG) model for medical imaging that automatically learns to focus on target structures of varying shapes and sizes.
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Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation
However, in most recent and promising techniques such as CNN based segmentation it is not obvious how to incorporate such prior knowledge.
