Article in Human brain mapping, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MICHAEL W WEINER · 2016 to 2026
$226.7M
Technology and Remote Assessment CoreU19AG063911 · NIA · MAYO CLINIC ROCHESTER · PI ADAM L. BOXER, Bradley F Boeve · 2019 to 2026
$120.9M
Early Onset AD Consortium - the LEAD Study (LEADS)U01AG057195 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI APOSTOLOVA, LIANA G, CARRILLO, MARIA C · 2018 to 2023
$70.3M
Smartphone-Based "Burst" Cognitive AssessmentsP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI Tammie Lee Smith Benzinger · 1985 to 2026
$69.5M
The Clinical Significance of Incidental White Matter Lesions on MRI Amongst a Diverse Population with Cognitive Complaints (INDEED)U19NS120384 · NINDS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Charles DeCarli · 2020 to 2026
$61.9M
THERAPEUTIC EFFECTS OF INTRA-NASAL INSULIN DETEMIRP50AG005136 · NIA · UNIVERSITY OF WASHINGTON · PI JAYADEY, SUMAN · 1985 to 2019
$57.2M
The natural history of AB accumulation in preclinical ADP01AG026276 · NIA · WASHINGTON UNIVERSITY · PI SCHINDLER, SUZANNE ELIZABETH · 2005 to 2025
$49.5M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
Satellite Diagnostic and Treatment Clinic CoreP50AG008702 · NIA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI DE JAGER, PHILIP L · 1989 to 2019
$46.3M
National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
TREATMENT OF DEPRESSION IN ALZHEIMER'S DISEASEP50AG005133 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SWEET, ROBERT A · 1985 to 2019
$43.0M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Artificial Intelligence Graduate School Program (Hanyang University), Ministry of Science and ICT (MSIT) RS-2020-II201373Artificial Intelligence Graduate School Program (Hanyang University), Ministry of Science and ICT (MSIT) RS-2023-00261368Hankuk University of Foreign Studies Research Fund of 2025Institute for Information & Communication Technology Planning & Evaluation (IITP), Ministry of Science and ICT (MSIT) IITP-(2025)-RS-2023-00253914Institute for Information & Communication Technology Planning & Evaluation (IITP), Ministry of Science and ICT (MSIT) RS-2024-00412644Korea Creative Content Agency (KOCCA), Ministry of Culture, Sports and Tourism (MCST) RS-2024-00332210Korea Health Industry Development Institute (KHIDI), Ministry of Health & Welfare (MOHW) RS-2025-02220534Korea National Institute of Health (KNIH) 2024ER040700Korea National Institute of Health (KNIH) 2025ER040300Ministry of Trade, Industry and Energy (MOTIE) RS-2025-13002970National Research Foundation of Korea (NRF), Ministry of Science and ICT (MSIT) RS-2024-00338048National Research Foundation of Korea (NRF), Ministry of Science and ICT (MSIT) RS-2024-00414119National Research Foundation of Korea (NRF), Ministry of Science and ICT (MSIT) RS-2024-00455720National Supercomputing Center, Korea Institute of Science and Technology Information KSC-2024-CRE-0021National Supercomputing Center, Korea Institute of Science and Technology Information KSC-2025-CRE-0065NCATS NIH HHS UL1 TR000448NCRR NIH HHS U24 RR021382NIA NIH HHS P01 AG003991NIA NIH HHS P01 AG026276NIA NIH HHS P20 AG068053NIA NIH HHS P20 AG068077NIA NIH HHS P20 AG068082NIA NIH HHS P30 AG010129NIA NIH HHS P30 AG010133NIA NIH HHS P30 AG010161NIA NIH HHS P30 AG013846NIA NIH HHS P30 AG013854NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG035982NIA NIH HHS P30 AG053760NIA NIH HHS P30 AG062421NIA NIH HHS P30 AG062422NIA NIH HHS P30 AG062428NIA NIH HHS P30 AG062429NIA NIH HHS P30 AG062677NIA NIH HHS P30 AG062715NIA NIH HHS P30 AG066444NIA NIH HHS P30 AG066462NIA NIH HHS P30 AG066468NIA NIH HHS P30 AG066506NIA NIH HHS P30 AG066507NIA NIH HHS P30 AG066508NIA NIH HHS P30 AG066509NIA NIH HHS P30 AG066511NIA NIH HHS P30 AG066512NIA NIH HHS P30 AG066514NIA NIH HHS P30 AG066515NIA NIH HHS P30 AG066518NIA NIH HHS P30 AG066519NIA NIH HHS P30 AG066530NIA NIH HHS P30 AG066546NIA NIH HHS P30 AG072931NIA NIH HHS P30 AG072946NIA NIH HHS P30 AG072947NIA NIH HHS P30 AG072958NIA NIH HHS P30 AG072959NIA NIH HHS P30 AG072972NIA NIH HHS P30 AG072973NIA NIH HHS P30 AG072975NIA NIH HHS P30 AG072976NIA NIH HHS P30 AG072977NIA NIH HHS P30 AG072978NIA NIH HHS P30 AG072979NIA NIH HHS P30 AG072980NIA NIH HHS P30 AG086401NIA NIH HHS P30 AG086404NIA NIH HHS P50 AG005133NIA NIH HHS P50 AG005136NIA NIH HHS P50 AG005142NIA NIH HHS P50 AG008702NIA NIH HHS P50 AG016573NIA NIH HHS P50 AG016574NIA NIH HHS P50 AG033514NIA NIH HHS P50 AG047266NIA NIH HHS P50 AG047270NIA NIH HHS P50 AG047366NIA NIH HHS R01 AG019771NIA NIH HHS R01 AG021910NIA NIH HHS R01 AG043434NIA NIH HHS R01 AG045571NIA NIH HHS R01 AG052560NIA NIH HHS R01 AG053509NIA NIH HHS R01 AG053993NIA NIH HHS R01 AG054110NIA NIH HHS R01 AG055005NIA NIH HHS R01 AG056031NIA NIH HHS R01 AG056258NIA NIH HHS R01 AG056531NIA NIH HHS R01 AG058724NIA NIH HHS R01 AG061788NIA NIH HHS R01 AG062276NIA NIH HHS R01 AG067781NIA NIH HHS R01 AG068338NIA NIH HHS R01 AG069453NIA NIH HHS R01 AG073235NIA NIH HHS R01 AG077444NIA NIH HHS R01 AG079280NIA NIH HHS R35 AG072262NIA NIH HHS R56 AG045571NIA NIH HHS U01 AG057195NIA NIH HHS U19 AG024904NIA NIH HHS U19 AG063911NIA NIH HHS U19 AG073153NIA NIH HHS U24 AG067418NIA NIH HHS U24 AG072122NIBIB NIH HHS R01 EB009352NIDCD NIH HHS R01 DC008552NIH HHS S10 OD026738NIMH NIH HHS P50 MH071616NINDS NIH HHS P30 NS098577NINDS NIH HHS R01 NS075075NINDS NIH HHS U19 NS120384RRD VA I01 RX001534RRD VA I21 RX001381
6 · The paper itself
Abstract
Positron emission tomography (PET) provides an in vivo molecular marker for various diseases, including Alzheimer's disease and related dementias (ADRD). PET has become increasingly integrated into diagnostic decision-making, disease staging, and clinical trial enrichment. However, its widespread use remains constrained by high costs, government regulations, and the invasiveness of radiotracer injection. Modern diagnostic frameworks emphasize the importance of multimodal biomarker assessment, such as the "amyloid/tau/neurodegeneration" (A/T/N) framework for Alzheimer's disease; however, they are constrained by these barriers. Medical image synthesis or translation offers a potential solution by enabling the reconstruction of unavailable modalities. The clinical utility of PET depends on accurately capturing regional uptake patterns rather than exact voxel-wise intensities, motivating the use of perceptual loss functions to assess higher-level semantic features in generative models. While 2D, 3D, and 2.5D perceptual losses are utilized in 3D synthesis, each encounters challenges, including limited volumetric context, the scarcity of pretrained 3D models, and difficulty balancing optimization across anatomical planes. In this work, we address cross-modal synthesis of tau PET from structural magnetic resonance imaging (MRI), generating 3D pseudo-[
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET. · full record | OpenQuestion