Evidence map›Paper›PMID 40129737›Full record

ArticleFrontiers in plant science2025

Combining multispectral and high-resolution 3D imaging for leaf vein segmentation and density measurement.

Yi-Hong Liao, Song Zhang

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. 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

2 authors.

Yi-Hong LiaoSchool of Mechanical Engineering, Purdue University, West Lafayette, IN, United States.
Song ZhangSchool of Mechanical Engineering, Purdue University, West Lafayette, IN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate leaf vein segmentation and vein density (VLA) measurement are crucial for understanding plant physiology. Traditional 2D imaging techniques often require labor-intensive and destructive processes, such as leaf flattening or chemical clearing, thereby limiting their practicality for high-throughput applications. In this study, we present a novel framework that integrates multispectral and high-resolution 3D imaging to enhance leaf vein segmentation and VLA measurement. By leveraging digital fringe projection, our system captures grayscale, multispectral, and 3D topographical data within a unified coordinate system. The integration of 3D information improves vein detection, particularly in low-contrast regions, while also enabling direct and accurate measurements of leaf area, vein length, and VLA. However, this approach also introduces some false positives in vein segmentation due to mesophyll surface variability. Despite these challenges, our high-resolution 3D imaging method shows significant potential for non-invasive phenotyping and trait assessment in complex, unstructured environments.

Indexed as

3D imaginghigh throughputleaf vein segmentationmultispectral imagingprecision agriculturestructured lightvein density

Identifiers

PMID40129737
PMCPMC11931515

What OpenQuestion holds

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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 OpenQuestion graph.