Evidence map›Paper›PMID 42361771›Full record

ArticleMedical image analysis2026

Beyond the LUMIR challenge: The pathway to foundational registration models.

Junyu Chen, Shuwen Wei, Joel Honkamaa, Pekka Marttinen, Hang Zhang, Min Liu, Yichao Zhou, Zuopeng Tan, Zhuoyuan Wang, Yi Wang and 26 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical image analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

36 authors.

Junyu ChenThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical School, Baltimore, MD, USA. Electronic address: jchen245@jhmi.edu.
Shuwen WeiImage Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.
Joel HonkamaaDepartment of Computer Science, Aalto University, Espoo, Uusimaa, Finland.
Pekka MarttinenDepartment of Computer Science, Aalto University, Espoo, Uusimaa, Finland.
Hang ZhangCornell University, New York, NY, USA.
Min LiuCollege of Electrical and Information Engineering, Hunan University, Changsha, Hunan, China.
Yichao ZhouCanon Medical Systems (China) Co. Ltd., Beijing, China.
Zuopeng TanCanon Medical Systems (China) Co. Ltd., Beijing, China.
Zhuoyuan WangSchool of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Yi WangSchool of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Hongchao ZhouSchool of Information Science and Engineering, Linyi University, Linyi, Shandong, China.
Shunbo HuSchool of Information Science and Engineering, Linyi University, Linyi, Shandong, China.
Yi ZhangDepartment of Imaging Physics, Delft University of Technology, Delft, South Holland, Netherlands.
Qian TaoDepartment of Imaging Physics, Delft University of Technology, Delft, South Holland, Netherlands.
Lukas FörnerDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg and Institute of Digital Medicine, Augsburg, Bavaria, Germany.
Thomas WendlerDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg and Institute of Digital Medicine, Augsburg, Bavaria, Germany.
Bailiang JianTechnical University of Munich and Klinikum Rechts der Isar, Munich, Bavaria, Germany.
Benedikt WiestlerTechnical University of Munich and Klinikum Rechts der Isar, Munich, Bavaria, Germany.
Tim HableInstitute of Medical Informatics, University of Lübeck, Lübeck, Schleswig-Holstein, Germany.
Jin KimDepartment of Radiology and Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA.
Dan RuanDepartment of Radiology and Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA.
Frederic MadestaInstitute for Applied Medical Informatics and Institute of Computational Neuroscience, University Medical Center Hamburg, Hamburg, Germany.
Thilo SentkerInstitute for Applied Medical Informatics and Institute of Computational Neuroscience, University Medical Center Hamburg, Hamburg, Germany.
Wiebke HeyerInstitute of Medical Informatics, University of Lübeck, Lübeck, Schleswig-Holstein, Germany.
Lianrui ZuoDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
Yuwei DaiRadboud University Medical Center, Nijmegen, Gelderland, Netherlands.
Jing WuDepartment of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA.
Jerry L PrinceImage Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.
Harrison BaiThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical School, Baltimore, MD, USA.
Yong DuThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical School, Baltimore, MD, USA.
Yihao LiuDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
Alessa HeringRadboud University Medical Center, Nijmegen, Gelderland, Netherlands.
Reuben DorentInria, Paris, France; Department of Neurosurgery, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA.
Lasse HansenEchoScout GmbH, Lübeck, Schleswig-Holstein, Germany.
Mattias P HeinrichInstitute of Medical Informatics, University of Lübeck, Lübeck, Schleswig-Holstein, Germany.
Aaron CarassImage Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.

Funding

MVP Data Integration into the ADSP Phenotype Harmonization ConsortiumU24AG074855 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CUCCARO, MICHAEL L, HOHMAN, TIMOTHY J · 2021 to 2025
$37.5M
Radiobioeffect Modeling of αRPTP01CA272222 · NCI · JOHNS HOPKINS UNIVERSITY · PI Ana Ponce Kiess · 2023 to 2026
$12.8M
1/3-Recurrence Markers, Cognitive Burden and Neurobiological Homeostasis in Late-life Depression (Rembrandt)R01MH121620 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI TAYLOR, WARREN D · 2020 to 2024
$5.3M
High Energy and Spatial Resolution Multi-Isotope SPECT Imaging of Targeted Alpha-Emitters and their DaughtersU01EB031798 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI DU, YONG, FREY, ERIC C. · 2021 to 2025
$3.8M
Novel Integrative Approach for the Early Detection of Lung Cancer using Repeated MeasuresR01CA253923 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LANDMAN, BENNETT A., MALDONADO, FABIEN · 2021 to 2025
$3.4M
Hyperspectral Single Photon Imaging of Targeted Alpha-EmittersR01EB031023 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI DU, YONG, GHALY, MICHAEL · 2021 to 2024
$2.7M
Integrating imaging and biopsy-derived molecular markers for the pre-surgical detection of indolent and aggressive early stage lung adenocarcinomaR01CA275015 · NCI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Marc Elliott Lenburg, Fabien Maldonado · 2023 to 2026
$2.6M
Artificial intelligence to estimate extent of cGVHD from patient photosR01HL169944 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Eric R Tkaczyk · 2024 to 2026
$2.3M
In Vivo 3-D Multi-Isotope Autoradiography of Radiopharmaceutical TherapyR01CA297470 · NCI · JOHNS HOPKINS UNIVERSITY · PI Yong Du, Quanzheng Li · 2025 to 2026
$1.1M
Employing quantitative image analysis based on deep learning to improve treatment efficacy in image-guided renal tumor ablationR03CA286693 · NCI · BROWN UNIVERSITY · PI BAI, HARRISON, KIMIA, BENJAMIN · 2024 to 2024
$165k
NCI NIH HHS P01 CA272222NCI NIH HHS R01 CA253923NCI NIH HHS R01 CA275015NCI NIH HHS R01 CA297470NCI NIH HHS R03 CA286693NHLBI NIH HHS R01 HL169944NIA NIH HHS U24 AG074855NIBIB NIH HHS R01 EB031023NIBIB NIH HHS U01 EB031798NIMH NIH HHS R01 MH121620
6 · The paper itself

Abstract

Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundational task in neuroimaging, has similarly advanced through the Learn2Reg initiative. Building on this, we introduce the Large-scale Unsupervised Brain MRI Image Registration (LUMIR) challenge, a next-generation benchmark for unsupervised brain MRI registration. Previous challenges relied upon anatomical label maps, however LUMIR provides 4,014 unlabeled T1-weighted MRIs for training, encouraging biologically plausible deformation modeling through self-supervision. Evaluation includes 590 in-domain test subjects and extensive zero-shot tasks across disease populations, imaging protocols, and species. Deep learning methods consistently achieved state-of-the-art performance and produced anatomically plausible, diffeomorphic deformation fields. They outperformed several leading optimization-based methods and remained robust to most domain shifts. These findings highlight the growing maturity of deep learning in neuroimaging registration and its potential to serve as a foundation model for general-purpose medical image registration.

Indexed as

BrainDeep LearningImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedMagnetic Resonance ImagingNeuroimagingUnsupervised Machine LearningAlgorithmsHumansFoundation modelsImage registrationMedical image challenges

Identifiers

PMID42361771
PMCPMC13419986

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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.