<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/CINECAstyle.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-24T10:17:51Z</responseDate><request verb="GetRecord" identifier="oai:iris.polito.it:11583/3011068" metadataPrefix="oai_dc">https://iris.polito.it/oai/request</request><GetRecord><record><header><identifier>oai:iris.polito.it:11583/3011068</identifier><datestamp>2026-05-19T11:26:31Z</datestamp><setSpec>com_11583_2614433</setSpec><setSpec>com_11583_2614425</setSpec><setSpec>col_11583_2614423</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title>Microwave imaging for breast cancer detection. Safety assessment, quantitative imaging, and breast density classification.</dc:title>
<dc:creator>RONCA, ALESSANDRA</dc:creator>
<dc:contributor>Ronca, Alessandra</dc:contributor>
<dc:contributor>ARDUINO, ALESSANDRO</dc:contributor>
<dc:contributor>TIBERI, GIANLUIGI</dc:contributor>
<dc:subject>quantitative imaging</dc:subject>
<dc:subject>  microwave imaging</dc:subject>
<dc:subject>  biomedical antenna</dc:subject>
<dc:subject>  dosimetry</dc:subject>
<dc:subject>  safety</dc:subject>
<dc:subject>  SAR</dc:subject>
<dc:subject>  temperature</dc:subject>
<dc:subject>  breast cancer</dc:subject>
<dc:subject>  contrast source inversion</dc:subject>
<dc:subject>  simulation</dc:subject>
<dc:subject>  experimental data</dc:subject>
<dc:subject>  breast density</dc:subject>
<dc:subject>  detection</dc:subject>
<dc:subject>  electrical propertie</dc:subject>
<dc:subject>  convolutional neural network</dc:subject>
<dc:subject>  deep learning</dc:subject>
<dc:subject>Settore IIET-01/A - Elettrotecnica</dc:subject>
<dc:description>L'abstract è  presente nell'allegato / the abstract is in the attachment</dc:description>
<dc:date>2026-04-28</dc:date>
<dc:type>info:eu-repo/semantics/doctoralThesis</dc:type>
<dc:identifier>https://hdl.handle.net/11583/3011068</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>firstpage:1</dc:relation>
<dc:relation>lastpage:243</dc:relation>
<dc:relation>numberofpages:243</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:publisher>Politecnico di Torino</dc:publisher>
<dc:publisher>country:Italy</dc:publisher>
<dc:rights>license:Creative commons</dc:rights>
<dc:rights>license:Creative commons</dc:rights>
<dc:rights>license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
<dc:rights>license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
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