Evidence map›Paper›PMID 42038796›Full record

ArticlePlant phenomics (Washington, D.C.)2026

Revealing hierarchical structure of leaf venations via diffusion-refined label-efficient segmentation: Dataset and method.

Weizhen Liu, Guangyu Lan, Zhiwen Xing, Jiayu Tan, Jiale Liu, Qingzhong Liu, Dongzi Zhu, Xiaohui Yuan, Nanqing Dong

Abstract read
In one paragraph

Article in Plant phenomics (Washington, D.C.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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.

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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.

Weizhen LiuSchool of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, Hubei, 430070, China.
Guangyu LanSchool of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, Hubei, 430070, China.
Zhiwen XingSchool of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, Hubei, 430070, China.
Jiayu TanSchool of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, Hubei, 430070, China.
Jiale LiuSchool of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, Hubei, 430070, China.
Qingzhong LiuShandong Key Laboratory of Fruit Biotechnology Breeding, Shandong Institute of Pomology, Taian, Shandong, 271000, China.
Dongzi ZhuShandong Key Laboratory of Fruit Biotechnology Breeding, Shandong Institute of Pomology, Taian, Shandong, 271000, China.
Xiaohui YuanYazhouwan National Laboratory, Sanya, Hainan, 572025, China.
Nanqing DongShanghai Innovation Institute, Shanghai, 200231, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In plant science, understanding the hierarchical structure of leaf venations is crucial for insights into plant physiology, evolution, and ecology. However, data-driven segmentation methods are hampered by the lack of specialized datasets for hierarchical leaf vein analysis. To address this, we introduce the

Indexed as

Diffusion refinementHierarchical segmentationLabel-efficient learningLeaf veinPartially supervision

Identifiers

PMID42038796
PMCPMC13109571

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.