<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Frontiers in Neurology &#8211; BIOENGINEER.ORG</title>
	<atom:link href="https://bioengineer.org/tag/frontiers-in-neurology/feed/" rel="self" type="application/rss+xml" />
	<link>https://bioengineer.org</link>
	<description>Bioengineering</description>
	<lastBuildDate>Fri, 16 Oct 2026 19:36:48 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</generator>

<image>
	<url>https://bioengineer.org/wp-content/uploads/2019/09/cropped-bioengineering-32x32.png</url>
	<title>Frontiers in Neurology &#8211; BIOENGINEER.ORG</title>
	<link>https://bioengineer.org</link>
	<width>32</width>
	<height>32</height>
</image> 
<site xmlns="com-wordpress:feed-additions:1">72741379</site>	<item>
		<title>Mamba-Powered Adaptation Turns Segment Anything Into an Automated Medical Lesion Segmenter</title>
		<link>https://bioengineer.org/mamba-powered-adaptation-turns-segment-anything-into-an-automated-medical-lesion-segmenter/</link>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Fri, 16 Oct 2026 19:36:48 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[computer-aided diagnosis]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[deep supervision]]></category>
		<category><![CDATA[domain adaptation]]></category>
		<category><![CDATA[Frontiers in Neurology]]></category>
		<category><![CDATA[lesion segmentation]]></category>
		<category><![CDATA[LoRA fine-tuning]]></category>
		<category><![CDATA[Mamba]]></category>
		<category><![CDATA[medical image segmentation]]></category>
		<category><![CDATA[Segment Anything Model]]></category>
		<category><![CDATA[state space models]]></category>
		<category><![CDATA[vision transformer]]></category>
		<guid isPermaLink="false">https://bioengineer.org/?p=423455</guid>

					<description><![CDATA[Researchers have adapted Meta's Segment Anything Model for medical imaging by combining low-rank fine-tuning, Mamba-based adapters, and a prompt-free decoder, achieving state-of-the-art lesion segmentation across six public datasets.]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">423455</post-id>	</item>
	</channel>
</rss>
