Evidence map›Paper›PMID 30619861›Full record

ArticleFrontiers in medicine2018

Tissue Intrinsic Fluorescence Spectra-Based Digital Pathology of Liver Fibrosis by Marker-Controlled Segmentation.

Takashi Saitou, Sota Takanezawa, Hiroko Ninomiya, Takao Watanabe, Shin Yamamoto, Yoichi Hiasa, Takeshi Imamura

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 20% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Phasor-FLIM and SHG imaging for quantitative analysis of lung cancer autofluorescence.Computational and structural biotechnology journal · 2025
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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

7 authors at 2 institutions in 1 country.

Takashi SaitouDepartment of Molecular Medicine for Pathogenesis, Graduate School of Medicine, Ehime University, Toon, Japan.
Sota TakanezawaDepartment of Molecular Medicine for Pathogenesis, Graduate School of Medicine, Ehime University, Toon, Japan.
Hiroko NinomiyaDepartment of Molecular Medicine for Pathogenesis, Graduate School of Medicine, Ehime University, Toon, Japan.
Takao WatanabeDepartment of Gastroenterology and Metabiology, Graduate School of Medicine, Ehime University, Toon, Japan.
Shin YamamotoDepartment of Gastroenterology and Metabiology, Graduate School of Medicine, Ehime University, Toon, Japan.
Yoichi HiasaDepartment of Gastroenterology and Metabiology, Graduate School of Medicine, Ehime University, Toon, Japan.
Takeshi ImamuraDepartment of Molecular Medicine for Pathogenesis, Graduate School of Medicine, Ehime University, Toon, Japan.
Ehime University · JPEhime University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tissue intrinsic emission fluorescence provides useful diagnostic information for various diseases. Because of its unique feature of spectral profiles depending on tissue types, spectroscopic imaging is a promising tool for accurate evaluation of endogenous fluorophores. However, due to difficulties in discriminating those sources, quantitative analysis remains challenging. In this study, we quantitatively investigated spectral-spatial features of multi-photon excitation fluorescence in normal and diseased livers. For morphometrics of multi-photon excitation spectra, we examined a marker-controlled segmentation approach and its application to liver fibrosis assessment by employing a mouse model of carbon tetrachloride (CCl

Indexed as

autofluorescencedigital pathologyimage segmentationliver fibrosismulti-photon microscopyspectral imaging

Identifiers

PMID30619861
PMCPMC6297145
OpenAlexW2905403119

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.