<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/8C5330CC-3C65-4205-963A-80D25B4D7415" ns1:id="8C5330CC-3C65-4205-963A-80D25B4D7415"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/FEBD57DF-9787-44B5-BCEE-87DBF71C4415" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6AD3147C-25BB-44F3-8788-395239A296AC" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6AD3147C-25BB-44F3-8788-395239A296AC" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2018-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/92F9130D-BC46-4EF3-AB78-4593770981BF" ns1:rel="FUND" ns1:start="2017-04-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">103311</ns2:identifier></ns2:identifiers><ns2:title>Enhanced mammography X-ray detector</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Mammography is a widely-adopted X-ray screening method used to detect and diagnose breast cancer earlier. Abnormalities in the breast are identified through contrast changes in the X-ray image. X-ray mammography is the only mass screening programme where patients are exposed to ionising radiation in a radio-sensitive organ, increasing the risk of radiation-induced cancer in healthy women. Mammograms are currently assessed subjectively which can lead to false positive/negatives in diagnosis, resulting in considerable distress and delay in treatment. IBEX have developed a core technology that can more accurately discriminate between tissue types and can improve image clarity to make it easier for clinicians to make accurate diagnoses. Additionally, the technology could be used to image patients at a lower dose than is currently used, further reducing the risk to women showing no symptoms during screening. This project aims to show that the materials information obtained is sufficiently sensitive to be able to discriminate between body fat and glandular tissue in the breast at lower patient doses</ns2:abstractText></ns2:project>