Ultrasound Entropy Imaging Based on the Kernel Density Estimation: A New Approach to Hepatic Steatosis Characterization.

Ruiyang Gao, Po-Hsiang Tsui, Shuicai Wu, Dar-In Tai, Guangyu Bin, Zhuhuang Zhou

Open access · goldAbstract read

In one paragraph

Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed, 1 pooled it

1.1field-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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

A Systematized Review of Quantitative Ultrasound Based on First-Order Speckle Statistics.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024
Pooled it

4 · The record

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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

6 authors at 2 institutions in 2 countries.

Ruiyang GaoDepartment of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China.

Po-Hsiang TsuiDepartment of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan.ORCID 0000-0002-5604-1800

Shuicai WuDepartment of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China.

Dar-In TaiDepartment of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan 333423, Taiwan.ORCID 0000-0003-1054-1583

Guangyu BinDepartment of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China.

Zhuhuang ZhouDepartment of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China.ORCID 0000-0003-0570-8473

Beijing University of Technology · CNChang Gung University · TW

Funding

Beijing Natural Science Foundation 4222001National Natural Science Foundation of China 11804013 and 61871005National Science and Technology Council in Taiwan NSTC 112-2221-E-182-006-MY3

6 · The paper itself

Abstract

In this paper, we present the kernel density estimation (KDE)-based parallelized ultrasound entropy imaging and apply it for hepatic steatosis characterization. A KDE technique was used to estimate the probability density function (PDF) of ultrasound backscattered signals. The estimated PDF was utilized to estimate the Shannon entropy to construct parametric images. In addition, the parallel computation technique was incorporated. Clinical experiments of hepatic steatosis were conducted to validate the feasibility of the proposed method. Seventy-two participants and 204 patients with different grades of hepatic steatosis were included. The experimental results show that the KDE-based entropy parameter correlates with log

Indexed as

backscatter envelope statisticshepatic steatosiskernel density estimationprobability density functionquantitative ultrasoundultrasound backscattered signalsultrasound entropy imagingultrasound tissue characterization

Identifiers

PMID38132230

DOI10.3390/diagnostics13243646

PMCPMC10742695

OpenAlexW4389618054

What OpenQuestion holds

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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.