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	<title>conditional GAN &#8211; BIOENGINEER.ORG</title>
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		<title>AI Learns to Fake Ultrasound Images to Spot Breast Tumors More Accurately</title>
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		<pubDate>Tue, 13 Oct 2026 03:11:49 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[BMC Medical Imaging]]></category>
		<category><![CDATA[Breast Cancer]]></category>
		<category><![CDATA[BUSI dataset]]></category>
		<category><![CDATA[computer-aided diagnosis]]></category>
		<category><![CDATA[conditional GAN]]></category>
		<category><![CDATA[convolutional neural network]]></category>
		<category><![CDATA[data augmentation]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[generative adversarial networks]]></category>
		<category><![CDATA[Medical Image Analysis]]></category>
		<category><![CDATA[tumor classification]]></category>
		<category><![CDATA[ultrasound imaging]]></category>
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					<description><![CDATA[Researchers in the Czech Republic have built a generative adversarial network that creates synthetic breast ultrasound images to train a lightweight classifier that reaches over 90 percent accuracy in distinguishing benign, malignant and normal tissue.]]></description>
		
		
		
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