Evidence map›Paper›PMID 33877970›Full record

ArticleIEEE transactions on ultrasonics, ferroelectrics, and frequency control2021

Noise Suppression for Ultrasound Attenuation Coefficient Estimation Based on Spectrum Normalization.

Ping Gong, Pengfei Song, Chengwu Huang, U-Wai Lok, Shanshan Tang, Chenyun Zhou, Lulu Yang, Kymberly D Watt, Matthew Callstrom, Shigao Chen

Abstract read
In one paragraph

Article in IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Ping Gong
Pengfei Song
Chengwu Huang
U-Wai Lok
Shanshan Tang
Chenyun Zhou
Lulu Yang
Kymberly D Watt
Matthew Callstrom
Shigao Chen

Funding

Ultrasound Evaluation of Liver SteatosisR21DK121943 · NIDDK · MAYO CLINIC ROCHESTER · PI CHEN, SHIGAO · 2020 to 2021
$437k
NIDDK NIH HHS R21 DK121943
6 · The paper itself

Abstract

Ultrasound attenuation coefficient estimation (ACE) has great diagnostic potential for fatty liver detection and assessment. In a previous study, we proposed a reference phantom-free ACE method, called reference frequency method (RFM), which does not require a calibrated phantom for normalization. The power of each frequency component can be normalized by the power of an adjacent frequency component in the spectrum to cancel system-dependent effects such as focusing and time gain compensation (TGC). RFM demonstrated accurate ACE in both phantom and in in-vivo liver studies. However, our study also showed that the robustness and penetration of RFM were affected by noise in the ACE signals. Here we propose a noise suppression (NS) and a signal-to-noise ratio (SNR) quality control method to reduce the influence of noise on ACE-RFM performance. The proposed methods were tested in harmonic ACE because harmonic imaging is a more frequently used mode than fundamental imaging for abdominal applications. After applying the NS and SNR control methods, the noise-induced bias for attenuation estimation in harmonic ACE was effectively reduced, leading to significantly improved effective penetration depth. The proposed methods directly measure the noise spectrum of the ultrasound system, which can also be adapted to other spectrum-based ACE methods, such as the reference phantom method and the spectra shift method.

Indexed as

LiverPhantoms, ImagingSignal-To-Noise RatioUltrasonography

Identifiers

PMID33877970
PMCPMC8344359

What OpenQuestion holds

Textmetadata
LicenceTDM
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.