Evidence map›Paper›PMID 38707197›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2024

Feature Extraction of Ultrasound Radiofrequency Data for the Classification of the Peripheral Zone of Human Prostate.

Teja Pathour, Ling Ma, Douglas W Strand, Jeffrey Gahan, Brett A Johnson, Shashank R Sirsi, Baowei Fei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2024. 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. Review
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.

Teja PathourCenter for Imaging and Surgical Innovation, The University of Texas at Dallas, TX.
Ling MaCenter for Imaging and Surgical Innovation, The University of Texas at Dallas, TX.
Douglas W StrandDepartment of Urology, The University of Texas Southwestern Medical Center, Dallas, TX.
Jeffrey GahanDepartment of Urology, The University of Texas Southwestern Medical Center, Dallas, TX.
Brett A JohnsonDepartment of Urology, The University of Texas Southwestern Medical Center, Dallas, TX.
Shashank R SirsiCenter for Imaging and Surgical Innovation, The University of Texas at Dallas, TX.
Baowei FeiCenter for Imaging and Surgical Innovation, The University of Texas at Dallas, TX.

Funding

ACADEMIC-INDUSTRIAL PARTNERSHIP FOR TRANSLATION OF PET/TRUS GUIDED INTERVENTIONR01CA204254 · NCI · UNIVERSITY OF TEXAS DALLAS · PI FEI, BAOWEI · 2017 to 2021
$2.0M
A Real-Time Hyperspectral Laparoscopic Stereo Imaging System for Robot-Assisted SurgeryR01CA288379 · NCI · UNIVERSITY OF TEXAS DALLAS · PI BAOWEI FEI · 2024 to 2026
$1.6M
NCI NIH HHS R01 CA204254NCI NIH HHS R01 CA288379
6 · The paper itself

Abstract

Prostate cancer ranks among the most prevalent types of cancer in males, prompting a demand for early detection and noninvasive diagnostic techniques. This paper explores the potential of ultrasound radiofrequency (RF) data to study different anatomic zones of the prostate. The study leverages RF data's capacity to capture nuanced acoustic information from clinical transducers. The research focuses on the peripheral zone due to its high susceptibility to cancer. The feasibility of utilizing RF data for classification is evaluated using

Indexed as

classificationperipheral zoneprostate cancerradiofrequency dataradiomicstissue characterizationUltrasound

Identifiers

PMID38707197
PMCPMC11069342

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.