Evidence map›Paper›PMID 41813694›Full record

ArticleScientific data2026

SMC-LUD:Large-Scale B-Mode Liver Ultrasound Dataset for Hepatocellular Carcinoma and Hemangioma Classification.

Jisoo Tak, Ryoung-Eun Ko, Ryan Donghan Kwon, Zeeshan Abbas, Yang Hyun Cho, Jongman Kim, Seondeok Seo, Namkee Oh, Seung Won Lee

Abstract readDataset
In one paragraph

Article in Scientific data, 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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

9 authors.

Jisoo Tak *Department of MetaBioBealth, Institute for Cross-disciplinary Studies, Sungkyunkwan University, Suwon, South Korea.ORCID http://orcid.org/0009-0004-6570-046X
Ryoung-Eun Ko *Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.ORCID http://orcid.org/0000-0003-4945-5623
Ryan Donghan KwonDepartment of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon, South Korea.ORCID http://orcid.org/0000-0003-3458-1301
Zeeshan AbbasDepartment of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon, South Korea.ORCID http://orcid.org/0000-0003-1472-183X
Yang Hyun ChoDepartment of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.ORCID http://orcid.org/0000-0003-1685-3641
Jongman KimDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.ORCID http://orcid.org/0000-0002-1903-8354
Seondeok SeoDepartment of Artificial Intelligence, Sungkyunkwan University, Suwon, South Korea.ORCID http://orcid.org/0009-0005-4850-3015
Namkee OhDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. ngnyou@gmail.com.ORCID http://orcid.org/0000-0002-6594-8973
Seung Won LeeDepartment of MetaBioBealth, Institute for Cross-disciplinary Studies, Sungkyunkwan University, Suwon, South Korea. swleemd@g.skku.edu.ORCID http://orcid.org/0000-0001-5632-5208

Funding

National Research Foundation of Korea (NRF) RS-2024-00341649Samsung SMX1230771
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally, and accurate classification of liver lesions using ultrasound remains challenging. We present SMC-LUD (Samsung Medical Center - Liver Ultrasound Dataset), a publicly available dataset of B-mode liver ultrasound images collected from Samsung Medical Center, Seoul, Korea, between 2015 and 2024. The dataset comprises 5,385 anonymized ultrasound images from 1,021 patients, categorized into two clinically relevant classes: hepatocellular carcinoma (images = 2,716) and hemangioma (images = 2,669). All HCC cases were histopathologically confirmed through surgical resection or biopsy, while hemangioma cases were radiologically diagnosed based on characteristic imaging features. Each image was labeled and verified by board-certified radiologists and pathologists. The dataset is organized with patient-level grouping. This resource addresses the scarcity of large, well-annotated ultrasound datasets for liver lesion classification and provides a valuable foundation for developing and validating deep learning models in liver cancer screening and diagnosis.

Indexed as

Carcinoma, HepatocellularHemangiomaLiver NeoplasmsHumansLiverRepublic of KoreaUltrasonography

Identifiers

PMID41813694
PMCPMC13111724

What OpenQuestion holds

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Registered trials

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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.