{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Tsai CH"],"funding":["National Health Research Institutes","National Science and Technology Council","Ministry of Education, Taiwan R.O.C."],"pagination":["e70168"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12660554"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["52(12)"],"pubmed_abstract":["<h4>Background</h4>Amyloid PET imaging has been extensively employed in the noninvasive assessment of amyloid-beta accumulation in Alzheimer's disease. Various amyloid radiotracers are commonly used in clinical settings; however, the limited interchangeability among these radiotracers hinders the feasibility of long-term clinical trials and multicenter comparisons. The Centiloid method was proposed for standardization, though providing a single score per image; voxel-wise translation remains a formidable task.<h4>Purpose</h4>This paper proposes a U-Net model based on a deformable convolution network (DCNv3-based U-Net) for [ 11C$^{11}\\textrm {C}$ ]-Pittsburgh compound B-to-[ 18F$^{18}\\textrm {F}$ ]-florbetaben image translation to augment existing datasets for large-scale model training an"],"journal":["Medical physics"],"pubmed_title":["Paired PET-MRI Deep Learning Model for Translating [&lt;sup&gt;11&lt;/sup&gt;C]PiB to [&lt;sup&gt;18&lt;/sup&gt;F]Florbetaben Amyloid Images."],"pmcid":["PMC12660554"],"funding_grant_id":["114-2628-E-002-019-MY3","NHRI-EX114- 11205EC","NTU-114L7872","NTU-114L900703","NTU-114V1015-5","NTU-113V1015-4"],"pubmed_authors":["Chen KT","Tsai CH","Huang SY","Hsiao IT","Wang HW","Lin YN"],"additional_accession":[]},"is_claimable":false,"name":"Paired PET-MRI Deep Learning Model for Translating [&lt;sup&gt;11&lt;/sup&gt;C]PiB to [&lt;sup&gt;18&lt;/sup&gt;F]Florbetaben Amyloid Images.","description":"<h4>Background</h4>Amyloid PET imaging has been extensively employed in the noninvasive assessment of amyloid-beta accumulation in Alzheimer's disease. Various amyloid radiotracers are commonly used in clinical settings; however, the limited interchangeability among these radiotracers hinders the feasibility of long-term clinical trials and multicenter comparisons. The Centiloid method was proposed for standardization, though providing a single score per image; voxel-wise translation remains a formidable task.<h4>Purpose</h4>This paper proposes a U-Net model based on a deformable convolution network (DCNv3-based U-Net) for [ 11C$^{11}\\textrm {C}$ ]-Pittsburgh compound B-to-[ 18F$^{18}\\textrm {F}$ ]-florbetaben image translation to augment existing datasets for large-scale model training an","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Dec","modification":"2026-06-06T07:17:17.598Z","creation":"2026-06-06T03:07:09.006Z"},"accession":"S-EPMC12660554","cross_references":{"pubmed":["41310910"],"doi":["10.1002/mp.70168"]}}