# Nuclide record idea-ai-lesion-segmentation-dosimetry (idea). Data CC BY-NC 4.0, attribute "Data from Nuclide (nuclide.cc)". Whole corpus: https://nuclide.cc/api/v1/nuclide.nt
@prefix schema: <https://schema.org/> .
@prefix nuclide: <https://nuclide.cc/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://nuclide.cc/ideas/idea-ai-lesion-segmentation-dosimetry/>
  a schema:CreativeWork ;
  nuclide:kind "idea" ;
  schema:identifier "idea-ai-lesion-segmentation-dosimetry" ;
  schema:name "AI segmentation to make voxel-level radioligand dosimetry practical at scale"@en ;
  schema:description "Working out how much radiation a patient's kidneys and tumours received after a radioactive treatment normally means a specialist spending hours tracing organ outlines by hand on a scan. Software that draws those outlines automatically using artificial intelligence can do the same job in minutes, making personalised dose tracking available everywhere, not just in a few specialist centres."@en ;
  schema:url <https://nuclide.cc/ideas/idea-ai-lesion-segmentation-dosimetry/> ;
  schema:dateModified "2026-09-22"^^xsd:date ;
  schema:citation <https://he01.tci-thaijo.org/index.php/bulletinAMS/article/view/279571>, <https://pmc.ncbi.nlm.nih.gov/articles/PMC10814892/>, <https://arxiv.org/abs/2603.22666>, <https://www.frontiersin.org/journals/nuclear-medicine/articles/10.3389/fnume.2026.1935247/full> ;
  nuclide:tag "artificial intelligence", "dosimetry", "segmentation" ;
  nuclide:related <https://nuclide.cc/technologies/radioligand-dosimetry/>, <https://nuclide.cc/technologies/in-vivo-dosimetry/>, <https://nuclide.cc/technologies/radiomics/>, <https://nuclide.cc/companies/mim-software/>, <https://nuclide.cc/technologies/quantitative-imaging-biomarkers/>, <https://nuclide.cc/isotopes/lu-177/> .