Evidence map›Paper›PMID 40891385›Full record

ArticleMagnetic resonance in medicine2026

Vessel segmentation for

Taechang Kim, Sooyeon Ji, Kyeongseon Min, Minjun Kim, Jonghyo Youn, Chungseok Oh, Jiye Kim, Jongho Lee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Magnetic resonance in medicine, 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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Vessel segmentation forMagnetic resonance in medicine · 2026
    Article
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

8 authors.

Taechang KimLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.ORCID 0009-0005-2257-7120
Sooyeon JiLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Kyeongseon MinLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Minjun KimLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Jonghyo YounLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Chungseok OhLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Jiye KimLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Jongho LeeLaboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.

Funding

AI-BIO Research Grant, Seoul National UniversityInstitute of Engineering Research, Seoul National UniversityInstitute of Information & communications Technology Planning & Evaluation IITP-2025-RS-2023-00256081Institute of New Media and Communication, Seoul National UniversityKorea Basic Science Institute RS-2024-00435727Korea Health Industry Development Institute RS-2024-00439677National Research Foundation of Korea RS-2024-00349509Samsung Electronics Co., Ltd IO201216-08215-01
6 · The paper itself

Abstract

purpose

methodsThe method comprises three steps: (1) seed generation from

resultsThe proposed method demonstrates superior performance to other vessel segmentation methods, effectively excluding the non-vessel structures, achieving the highest Dice score coefficient against manually segmented vessel masks (3 T: 76.7% for

conclusionThe proposed method has the potential to facilitate various applications, offering reliable analysis through the generation of a high-quality vessel mask.

Indexed as

Blood VesselsBrainImage Processing, Computer-AssistedMagnetic Resonance ImagingAlgorithmsArtifactsHumansIronMyelin SheathReproducibility of ResultsIronimage analysisvessel segmentationx‐separation

Identifiers

PMID40891385
PMCPMC12620182

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.