Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study

Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms wer...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computer modeling in engineering & sciences 2022, Vol.130 (1), p.397-413
Hauptverfasser: Zheng, Chichao, Wang, Yazhong, Wang, Yadan, He, Qing, Peng, Hu
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 413
container_issue 1
container_start_page 397
container_title Computer modeling in engineering & sciences
container_volume 130
creator Zheng, Chichao
Wang, Yazhong
Wang, Yadan
He, Qing
Peng, Hu
description Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total LRLs strength. The aGCF-weighted VS (aGCF-VS) images were compared with standard VS images and GCF-weighted VS (GCF-VS) images. Simulation and experimental results demonstrated that the contrast ratio (CR) and contrast-to-noise ratio (CNR) of aGCF-VS are greatly improved, compared with standard VS imaging. And in comparison with GCF-VS, aGCF-VS can obtain better CNR and speckle signal-to-noise ratio (sSNR) while maintaining similar CR. Therefore, aGCF is suitable for VS imaging to improve contrast and preserve speckle pattern.
doi_str_mv 10.32604/cmes.2022.016308
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2604980189</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2604980189</sourcerecordid><originalsourceid>FETCH-LOGICAL-c268t-27f0773a9b14bd4dd8e9c7864814fd3c8b96c6ae600996bb714866410ac6b8603</originalsourceid><addsrcrecordid>eNpNkEFPwzAMhSMEEmPwA7hF4rzhNJ2bcJumDSZN4jDGNUrTdHRa05KkiP17WsaBi23JT8_PHyH3DKY8QUgfTW3DNIEkmQJDDuKCjNgswQmbAV7-m6_JTQgHAI5cyBEp54VuY_Vl6XvlY6ePdNt03li6rvW-cnu6C0ONH5Zu7Wdn3bBy0bpQxRNdaRMb_0S3Vd0ddawaR7Ur6PK7tb6qrYuDX-yK0y25KvUx2Lu_Pia71fJt8TLZvD6vF_PNxCQo4iTJSsgyrmXO0rxIi0JYaTKBqWBpWXAjcokGtUUAKTHPM5YKxJSBNpgLBD4mD2ff1jd92hDVoX_H9SfVQEkKYEL2KnZWGd-E4G2p2j6u9ifFQP3iVANONeBUZ5z8B-XRaVM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2604980189</pqid></control><display><type>article</type><title>Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study</title><source>Tech Science Press</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Zheng, Chichao ; Wang, Yazhong ; Wang, Yadan ; He, Qing ; Peng, Hu</creator><creatorcontrib>Zheng, Chichao ; Wang, Yazhong ; Wang, Yadan ; He, Qing ; Peng, Hu</creatorcontrib><description>Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total LRLs strength. The aGCF-weighted VS (aGCF-VS) images were compared with standard VS images and GCF-weighted VS (GCF-VS) images. Simulation and experimental results demonstrated that the contrast ratio (CR) and contrast-to-noise ratio (CNR) of aGCF-VS are greatly improved, compared with standard VS imaging. And in comparison with GCF-VS, aGCF-VS can obtain better CNR and speckle signal-to-noise ratio (sSNR) while maintaining similar CR. Therefore, aGCF is suitable for VS imaging to improve contrast and preserve speckle pattern.</description><identifier>ISSN: 1526-1506</identifier><identifier>ISSN: 1526-1492</identifier><identifier>EISSN: 1526-1506</identifier><identifier>DOI: 10.32604/cmes.2022.016308</identifier><language>eng</language><publisher>Henderson: Tech Science Press</publisher><subject>Adaptive algorithms ; Beamforming ; Eigenvalues ; Image contrast ; Image enhancement ; Image quality ; Image resolution ; Signal to noise ratio ; Simulation ; Speckle patterns ; Synthetic apertures ; Ultrasonic imaging</subject><ispartof>Computer modeling in engineering &amp; sciences, 2022, Vol.130 (1), p.397-413</ispartof><rights>2022. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c268t-27f0773a9b14bd4dd8e9c7864814fd3c8b96c6ae600996bb714866410ac6b8603</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,4010,27904,27905,27906</link.rule.ids></links><search><creatorcontrib>Zheng, Chichao</creatorcontrib><creatorcontrib>Wang, Yazhong</creatorcontrib><creatorcontrib>Wang, Yadan</creatorcontrib><creatorcontrib>He, Qing</creatorcontrib><creatorcontrib>Peng, Hu</creatorcontrib><title>Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study</title><title>Computer modeling in engineering &amp; sciences</title><description>Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total LRLs strength. The aGCF-weighted VS (aGCF-VS) images were compared with standard VS images and GCF-weighted VS (GCF-VS) images. Simulation and experimental results demonstrated that the contrast ratio (CR) and contrast-to-noise ratio (CNR) of aGCF-VS are greatly improved, compared with standard VS imaging. And in comparison with GCF-VS, aGCF-VS can obtain better CNR and speckle signal-to-noise ratio (sSNR) while maintaining similar CR. Therefore, aGCF is suitable for VS imaging to improve contrast and preserve speckle pattern.</description><subject>Adaptive algorithms</subject><subject>Beamforming</subject><subject>Eigenvalues</subject><subject>Image contrast</subject><subject>Image enhancement</subject><subject>Image quality</subject><subject>Image resolution</subject><subject>Signal to noise ratio</subject><subject>Simulation</subject><subject>Speckle patterns</subject><subject>Synthetic apertures</subject><subject>Ultrasonic imaging</subject><issn>1526-1506</issn><issn>1526-1492</issn><issn>1526-1506</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpNkEFPwzAMhSMEEmPwA7hF4rzhNJ2bcJumDSZN4jDGNUrTdHRa05KkiP17WsaBi23JT8_PHyH3DKY8QUgfTW3DNIEkmQJDDuKCjNgswQmbAV7-m6_JTQgHAI5cyBEp54VuY_Vl6XvlY6ePdNt03li6rvW-cnu6C0ONH5Zu7Wdn3bBy0bpQxRNdaRMb_0S3Vd0ddawaR7Ur6PK7tb6qrYuDX-yK0y25KvUx2Lu_Pia71fJt8TLZvD6vF_PNxCQo4iTJSsgyrmXO0rxIi0JYaTKBqWBpWXAjcokGtUUAKTHPM5YKxJSBNpgLBD4mD2ff1jd92hDVoX_H9SfVQEkKYEL2KnZWGd-E4G2p2j6u9ifFQP3iVANONeBUZ5z8B-XRaVM</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Zheng, Chichao</creator><creator>Wang, Yazhong</creator><creator>Wang, Yadan</creator><creator>He, Qing</creator><creator>Peng, Hu</creator><general>Tech Science Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>2022</creationdate><title>Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study</title><author>Zheng, Chichao ; Wang, Yazhong ; Wang, Yadan ; He, Qing ; Peng, Hu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c268t-27f0773a9b14bd4dd8e9c7864814fd3c8b96c6ae600996bb714866410ac6b8603</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adaptive algorithms</topic><topic>Beamforming</topic><topic>Eigenvalues</topic><topic>Image contrast</topic><topic>Image enhancement</topic><topic>Image quality</topic><topic>Image resolution</topic><topic>Signal to noise ratio</topic><topic>Simulation</topic><topic>Speckle patterns</topic><topic>Synthetic apertures</topic><topic>Ultrasonic imaging</topic><toplevel>online_resources</toplevel><creatorcontrib>Zheng, Chichao</creatorcontrib><creatorcontrib>Wang, Yazhong</creatorcontrib><creatorcontrib>Wang, Yadan</creatorcontrib><creatorcontrib>He, Qing</creatorcontrib><creatorcontrib>Peng, Hu</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Computer modeling in engineering &amp; sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zheng, Chichao</au><au>Wang, Yazhong</au><au>Wang, Yadan</au><au>He, Qing</au><au>Peng, Hu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study</atitle><jtitle>Computer modeling in engineering &amp; sciences</jtitle><date>2022</date><risdate>2022</risdate><volume>130</volume><issue>1</issue><spage>397</spage><epage>413</epage><pages>397-413</pages><issn>1526-1506</issn><issn>1526-1492</issn><eissn>1526-1506</eissn><abstract>Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total LRLs strength. The aGCF-weighted VS (aGCF-VS) images were compared with standard VS images and GCF-weighted VS (GCF-VS) images. Simulation and experimental results demonstrated that the contrast ratio (CR) and contrast-to-noise ratio (CNR) of aGCF-VS are greatly improved, compared with standard VS imaging. And in comparison with GCF-VS, aGCF-VS can obtain better CNR and speckle signal-to-noise ratio (sSNR) while maintaining similar CR. Therefore, aGCF is suitable for VS imaging to improve contrast and preserve speckle pattern.</abstract><cop>Henderson</cop><pub>Tech Science Press</pub><doi>10.32604/cmes.2022.016308</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1526-1506
ispartof Computer modeling in engineering & sciences, 2022, Vol.130 (1), p.397-413
issn 1526-1506
1526-1492
1526-1506
language eng
recordid cdi_proquest_journals_2604980189
source Tech Science Press; EZB-FREE-00999 freely available EZB journals
subjects Adaptive algorithms
Beamforming
Eigenvalues
Image contrast
Image enhancement
Image quality
Image resolution
Signal to noise ratio
Simulation
Speckle patterns
Synthetic apertures
Ultrasonic imaging
title Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T04%3A31%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Adaptive%20Virtual%20Source%20Imaging%20Using%20the%20Sequence%20Intensity%20Factor:%20Simulation%20and%20Experimental%20Study&rft.jtitle=Computer%20modeling%20in%20engineering%20&%20sciences&rft.au=Zheng,%20Chichao&rft.date=2022&rft.volume=130&rft.issue=1&rft.spage=397&rft.epage=413&rft.pages=397-413&rft.issn=1526-1506&rft.eissn=1526-1506&rft_id=info:doi/10.32604/cmes.2022.016308&rft_dat=%3Cproquest_cross%3E2604980189%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2604980189&rft_id=info:pmid/&rfr_iscdi=true