Article

Breast Abnormality Classification in Resource-Constrained Settings Through GAN Generated Synthetic Mammography Patches

2026-07-09

Abstract excerpt

<title>Abstract</title> <p>Developing deep learning (DL) models for medical imaging is often hindered by limited resources because it requires substantial computing resources and sufficient training data. We propose the use of low-resource-consuming Generative Adversarial Network (GAN) to generate synthetic medical image patches to train mammography patch classifier to classify abnormal and normal breast mammogra...

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Literature Corpus work: 07482fd5-7317-5009-afeb-7346bd950d46
DOI: 10.21203/rs.3.rs-10293673/v1

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