Article in Proceedings. IEEE International Symposium on Biomedical Imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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.
Zhen ZhouAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Jian LiAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Jonathan WilliamsAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Bruce FischlAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Iman AganjAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Funding
Functionally guided adult whole brain cell atlas in human and NHPUM1MH130981 · NIMH · ALLEN INSTITUTE · PI Ed Lein, Hongkui Zeng · 2022 to 2026
$91.9M
Center for Multi-Scale Multi-Omic Human and non-human primate Brain AtlasUM1MH134812 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Kwanghun Chung, PATRICK R HOF · 2025 to 2026
$21.7M
BRAIN CONNECTS: The center for Large-scale Imaging of Neural Circuits (LINC)UM1NS132358 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Suzanne N Haber, Elizabeth M. C. Hillman · 2023 to 2026
$17.5M
MRI, Genetics &Cognitive Precursors of AD &DementiaR01AG016495 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA · 1999 to 2016
$12.5M
The Human Connectome Project (HCP)U01MH093765 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2010 to 2014
$12.1M
Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BRUCE R ROSEN · 2020 to 2026
$10.9M
Late-onset Unexplained Epilepsy as a Risk Factor for DementiaR01NS130119 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Alice D Lam · 2023 to 2026
$8.7M
Imaging and Analysis Techniques to Construct a Cell Census Atlas of the Human Brain Admin SupplementU01MH117023 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI BOAS, DAVID A, FISCHL, BRUCE · 2018 to 2022
$7.6M
An Acquisition and Analysis Pipeline for Integrating MRI and Neuropathology in TBI-related Dementia and VCIDU24NS135561 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl, Susie Yi Huang · 2023 to 2026
$6.1M
FreeSurfer Development, Maintenance, and HardeningR01EB023281 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl, Douglas Nowlin Greve · 2016 to 2026
$5.6M
Clinical & biological signatures of post-traumatic neurodegeneration: Leveraging the TBI Model Systems of Care to accelerate in vivo diagnosis of the late effects of TBI (LETBI)RF1NS128961 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI DAMS-O'CONNOR, KRISTEN · 2022 to 2022
$5.0M
A Longitudinal Analysis Stream for FreeSurferR01NS083534 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl · 2014 to 2026
Accurate cortical surface registration is crucial for group-level neuroimaging analyses, yet geometry-based methods often yield suboptimal functional alignment across subjects due to substantial inter-individual variability. We present a novel deep-learning approach that incorporates white matter structural connectivity features from diffusion MRI (dMRI) tractography into the Joint Surface-based Registration and Atlas Construction (JOSA) framework. Our method generates vertex-wise connectivity maps by detecting streamline-surface intersections, followed by heat diffusion smoothing on the cortical manifold. We combine these connectivity features with scalar diffusion metrics (fractional anisotropy and apparent diffusion coefficient) and structural features as input to JOSA (which we call "JOSAConn"). Evaluated on HCP-YA subjects across 15 task contrasts, our method significantly outperforms FreeSurfer in functional alignment (Bonferroni-corrected
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.
DEEP-LEARNING CORTICAL REGISTRATION GUIDED BY STRUCTURAL AND DIFFUSION MRI AND CONNECTIVITY. · full record | OpenQuestion