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Found 6 papers, 5 papers with code
ExplainFix: Explainable Spatially Fixed Deep Networks
We are first to demonstrate that all spatial filters in state-of-the-art convolutional deep networks can be fixed at initialization, not learned.
HeartSpot: Privatized and Explainable Data Compression for Cardiomegaly Detection
HeartSpot priors are ante-hoc explainable and give a human-interpretable image of the preserved spatial features that clearly outlines the heart.
Enhancement of Retinal Fundus Images via Pixel Color Amplification
We propose a pixel color amplification theory and family of enhancement methods to facilitate segmentation tasks on retinal images.
Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
Diabetic Retinopathy (DR) is a leading cause of blindness in working age adults.
Learned Pre-Processing for Automatic Diabetic Retinopathy Detection on Eye Fundus Images
Diabetic Retinopathy is the leading cause of blindness in the working-age population of the world.
O-MedAL: Online Active Deep Learning for Medical Image Analysis
Our online method enhances performance of its underlying baseline deep network.
