[go: up one dir, main page]

WO2025024362A2 - Apprentissage profond pour imagerie de vitesse sonore à l'aide d'ultrasons à écho d'impulsion - Google Patents

Apprentissage profond pour imagerie de vitesse sonore à l'aide d'ultrasons à écho d'impulsion Download PDF

Info

Publication number
WO2025024362A2
WO2025024362A2 PCT/US2024/038975 US2024038975W WO2025024362A2 WO 2025024362 A2 WO2025024362 A2 WO 2025024362A2 US 2024038975 W US2024038975 W US 2024038975W WO 2025024362 A2 WO2025024362 A2 WO 2025024362A2
Authority
WO
WIPO (PCT)
Prior art keywords
neura
meo
mas
cams
orevce
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/US2024/038975
Other languages
English (en)
Other versions
WO2025024362A3 (fr
Inventor
Aiguo HAN
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Virginia Tech Intellectual Properties Inc
Original Assignee
Virginia Tech Intellectual Properties Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Virginia Tech Intellectual Properties Inc filed Critical Virginia Tech Intellectual Properties Inc
Publication of WO2025024362A2 publication Critical patent/WO2025024362A2/fr
Publication of WO2025024362A3 publication Critical patent/WO2025024362A3/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/772—Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8909—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using a static transducer configuration
    • G01S15/8915—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using a static transducer configuration using a transducer array
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8995—Combining images from different aspect angles, e.g. spatial compounding
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
    • G01S7/52023—Details of receivers
    • G01S7/52036—Details of receivers using analysis of echo signal for target characterisation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
    • G01S7/52046—Techniques for image enhancement involving transmitter or receiver
    • G01S7/52049—Techniques for image enhancement involving transmitter or receiver using correction of medium-induced phase aberration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
    • G01S7/52053—Display arrangements
    • G01S7/52057—Cathode ray tube displays
    • G01S7/52071—Multicolour displays; using colour coding; Optimising colour or information content in displays, e.g. parametric imaging
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Definitions

  • roenar-owoer smuaon envronmens unerscores aeneraza caene wenransonnro aa.sscreanc roo cause oe caenese comex o smuam smuaonso exermenaaa. roeres var acrossssues an remana nmae mea, were acousc unreasc assumons on a ro accurae ancae.revaen ase are, eor, cannrouce consceorausecroereernceess, en.
  • ecoes.eseerences cons usome-ro.-, ecoes asnu euen, neavemac neura neworsarec useuse seccmen-sse.a m oea ussunrem raewns c asan nneewoara,nus.nvesnoena exsnores oeeea o usscnaroman- ae saa varaon oo causes ssnraveme.srnceas rec nceoeveo non- aroacesoroman.erenenvenorr eneen use a reconsrucsosruonromme-s mas.e ooses a ramewor anmae-o-
  • noresns an aroaca uses waserorme a mue m-anes, ecca, common m-aneeamormn common m-aneeamorm eacen a unueme-s ma.so,e use o omeecnuesnncu eneanocseessecousaen omea-s mas. an,, useaen ca enos.,, , caonuc ono. nernaonaaen .snevs,.aoanu, ao.
  • meo orevce o an osecs- did one or more or eac vecorzaoen.ca anor smuaeme-s masserve usnnamcrorammn anor maservese ucsnsnea meo orevce o an osecs-, dide measureme-s sec smec merooram ormnev anor vecorzaon.
  • neworsrane convern a reresencaev oe amne- oss meacsn-o, an woere mnaeneuen neura o mano aeorecame-s ma moe oann areceme-s e ma an comarn an mnmzn anerenceewee maoreo reresenave nereceme-s ma ane worsrasemce-s ma. ne se meo orevce o an osecs-, dideee neura osneecsaaea mraeeosm onvovn mue s.
  • ne an osecs- were reconsruce me-s ma or mue measureme-s masee an neu nroa neeomweorrc on: oonrma a sonn oe measureoemae.
  • e oecs use asusaencce ansore meeeeo ne ourrevce o an osecs-, were no-moemae aasnas.
  • ra newor e., oneeoreca urasoun orneoceo.:usome- - sec se meo orevce ro., neworas a-ne a o an osecs-, dideee neura neworas asecrcseec muree.o orevce o an osecs-, dideee neura eee neursec arcseec muere.o orevce o an osecs-, didaaroveor sae nceworsser moveen a raoußc orma.
  • a measureme-s ma eneraen a moe wou cons aneroun-ruo ma .ecnuene m.oe-s a acrceormnaeso soewrnn axeenae. o usne mrrore Receive aerure . emomens oenvenon. .s a-n auresr aaoenor oecxa anme-xs. ma ., a measureme-s ma accou.n., ane reconsruceo ma .
  • ncaesa a sma-numereaso a smaer sece numer.
  • erormance oe sece-racn aorm sze, wc mace wereer accroua or narrow a .n aon,e-numermacsexao mo nereoreexmeea.
  • orneoceo e sseween aacenx anes are sue, soe w us- - anes.em omero., aneme s ma was o ere concaenaeoeer acar, comaneeween°x ane an°x ane. ouuarorranne nresunra a nemwe-s ma an aroun-ruo ma, serves as annu- .eworrann anor.
  • oroeesruon:oo mean suare error vsuazen..uc ao can o a ,e amon erenorouss .renz,.aeer, “m soeounn e a..
  • anrenz “owars errasoncs, v oe:namc rane areac reucon,”n o.,.–, oowa,.. aneze,.., “e convouona s.reea.on oo. r,e vos.raon-aseane wave seereuse-ecooca soun see esmaors,” recon oeamorme, no. w,en.
  • an,es are c.anee ar.aoc a arsreesssromsse roae oscaon oeresennvenon,e meo uze sue,n emomens aeer, aun,.. s a common m-aneracn aroac , common-mon snas,” e a.,r “ansv.ereee.rmmnaene,a vs-suares aerraon esmaes usn a anse oscaonrecon oes.s aro., no.,.
  • neecona eaceconocncue a ⁇ ransose con uce overn.
  • sre o anwo ⁇ convouonaaers w anan.na,vouonaaer w a were ae ase ouuaer.erarameers oe ⁇ convouonaaersncun u-wave smuaon sames.
  • rass weaa u szneesnsc waa om s a aruamen n-ra eao ra cn uorem, reusuaonn.n aeneasrcs moe assumn sra rou marx mucaon.sorwar moe was em orwar moe acae mas.srocessnvoves anearra oeo eceneneraeme-s me-s mas, re nsormaon aeoo masorouce corresonn mnue urnessan.
  • monnu-o were convereome-s mas..s a resu, were use uuars were snesze.ese sneszenu-ouuars u comuoa exoneansv-eexenresrvaenue-w neaentea s nmeuwaore. samersrerann sae,e more accurae moe. ears wereen useone-unee orzonammee,r.e coureresoonen smmmee-sr o maeman ssem, wen ano mas onu-ouu mas caneenerae.
  • mas are cacuae usn rresonn ra-racn sneszeme-s snesz.em e sae-o-e-arnearorwar moe , .nverne roem e-s maso ano ma,e s essena sovnenearorwar eo maosnaensave comesceaeearnaner cnas.aesees oo ma,sm we-esree mraves wereeneraerom aase.oa o. mon sames,ncuneo mas ane romemaee me-s mas, were useorane moe.
  • rous moes suoseo accurae o assesse moe's rousnroemss, o a ceorn coronce snu aco wuasscerroveer wese anman ssem sens.
  • consan we oerarameers were m reneo mas remane conssen oucom oe.
  • rous moes execeorouce reave meumroereses a.nus sseu se was conucen smuaonueoe convenence o ausn woes oucuansn smuaons.
  • anues se ons were smuaeoes moe rousness:enssruon roaaon.ennss.
  • -aanscees onversree reconsrucon meos were comare asoows: a eeo ma, ona aesnearrorammn oneme-s maso a useseme-s m usan a csanenenaua, a asccoernnu,o an emoemernosos oeesncvse-nue caracerscs oeseree meos are summar on.e ae.ummar oee zenae.
  • eo nuconsruconreos scs-asenverson me-s mas a-rae asssumon oenenaerar was oane sovn anear omzao .
  • a reconsruconorman see-o-soun wnrouseem-ecoan uarraaso,un.:. em au.,aaaoman su,”s.e.o., vo., no.,. , , .oowon ann vvo ,eroem was sove usn ooox, ascne c nanara, rameworran,.
  • s eos were seoavee same ouu sze o s reon wasocae aeners ocaene cener oenume-s mas. .rovese exeemcoanr ooe maanse waves w erenx anes. reconsruceo mas sare smar oaneromeesn se.sua,e rououe,es samesee aes werounrus.uanave evauaonoerounruo vaues, roo mean suare error o.
  • ms.eave o..eow e reconsruconae roo mean suareercen error roemoroman errorsncaee caa o n sovne casscnverse error concenra ceoss oen exea.monomn reeo renc.onssru ecrreor aoe mao,oms oserveae reconsrucon me-s sna occursneoseror reon, reons exece,venae eneaem. su usn scs wereaseoomxesaceoseror reon aeer,.
  • saseroun-ruo mas ane reconsruceo mas were c row corresonso aeren aanom.na, aneaze conon was ennseraerne, weorsaennensaa. assuomweveorn, ann reaus,e sreoenrses w oereee mnecaoose useor sruon var acrossssues, maneseroere umsuc asens e cenerußc oeuse canevaer s caenno ancae.
  • aouencusons are no as saen,ere are anoemen caonrasans roemco.nsorrucee onreasncuson re e mmcn conon cos.nras,e canne-aa aroaca caenesnsnusnssue- vmeraar,meens.
  • oeer emomens oenvenon we aarenoose sene s noenar scuecarcaao wn aenre ar raacncee o o vaeuensvesnroonv.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Evolutionary Computation (AREA)
  • Acoustics & Sound (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Databases & Information Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Molecular Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Professional, Industrial, Or Sporting Protective Garments (AREA)
  • Ultra Sonic Daignosis Equipment (AREA)

Abstract

L'invention concerne des procédés de création d'un réseau neuronal profond entraîné, dans des modes de réalisation, les procédés consistant à : fournir un certain nombre d'images naturelles; convertir chaque image naturelle en une carte de vitesse de son (SoS); pour chacune des cartes SoS, dériver une carte de décalage temporel théorique; et entraîner un réseau neuronal profond sur la base de paires de cartes de décalage temporel et de SoS, chacune des paires comprenant l'une des cartes de décalage temporel théoriques et sa carte SoS correspondante; le réseau neuronal profond étant capable de reconstruire une image de vitesse de son (SoS) à partir d'une carte de décalage temporel mesuré générée à partir d'ultrasons.
PCT/US2024/038975 2023-07-21 2024-07-22 Apprentissage profond pour imagerie de vitesse sonore à l'aide d'ultrasons à écho d'impulsion Pending WO2025024362A2 (fr)

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US202363515012P 2023-07-21 2023-07-21
US63/515,012 2023-07-21
US202463574759P 2024-04-04 2024-04-04
US63/574,759 2024-04-04
US202463649788P 2024-05-20 2024-05-20
US63/649,788 2024-05-20

Publications (2)

Publication Number Publication Date
WO2025024362A2 true WO2025024362A2 (fr) 2025-01-30
WO2025024362A3 WO2025024362A3 (fr) 2025-04-24

Family

ID=94375399

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2024/038975 Pending WO2025024362A2 (fr) 2023-07-21 2024-07-22 Apprentissage profond pour imagerie de vitesse sonore à l'aide d'ultrasons à écho d'impulsion

Country Status (1)

Country Link
WO (1) WO2025024362A2 (fr)

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8079263B2 (en) * 2006-11-10 2011-12-20 Penrith Corporation Transducer array imaging system
KR102380167B1 (ko) * 2019-12-13 2022-03-29 한국과학기술원 단일 초음파 프로브를 이용한 정량적 이미징 방법 및 장치
US12144685B2 (en) * 2019-12-13 2024-11-19 Korea Advanced Institute Of Science And Technology Method and apparatus for quantitative ultrasound imaging using single-ultrasound probe

Also Published As

Publication number Publication date
WO2025024362A3 (fr) 2025-04-24

Similar Documents

Publication Publication Date Title
CN110599263B (zh) 用户互动数据处理方法、装置、存储介质和计算机设备
CN104683537B (zh) 一种号码标记方法及装置
CN104702804B (zh) 一种号码标记方法及装置
CN109711746A (zh) 一种基于复杂网络的信用评估方法和系统
CN106856439A (zh) 一种方案测试的方法及服务器
WO2025112726A1 (fr) Procédé et système de planification de stockage orienté consommation d'énergie photovoltaïque distribuée pour réseau de distribution flexible
WO2025024362A2 (fr) Apprentissage profond pour imagerie de vitesse sonore à l'aide d'ultrasons à écho d'impulsion
CN117351474A (zh) 基于图像处理的烤烟叶斑病害的检测方法
CN110163844A (zh) 眼底病灶检测方法、装置、计算机设备及存储介质
CN115035309A (zh) 一种水稻病害识别方法及装置
CN117994650A (zh) 基于大数据的智能农业管理系统
CN113256431A (zh) 一种基于平行链技术的供应链金融服务方法及装置
CN109544326A (zh) 业务请求响应方法、装置、计算机设备和存储介质
CN109754135A (zh) 信用行为数据处理方法、装置、存储介质和计算机设备
CN116152198A (zh) 一种基于Wave-SubNet轻量级模型的番茄叶斑病识别方法
Jia et al. Large language model strategic reasoning evaluation through behavioral game theory
CN108694124A (zh) 一种基于Mock的房产交易系统测试数据构造方法及系统
CN109670961A (zh) 投后管理方法、装置、终端设备及计算机可读存储介质
CN108415965A (zh) 一种基于多数据源的数据处理方法和装置
CN106776069A (zh) 一种软件系统间自动收集传输数据的方法及系统
CN110348854A (zh) 一种基于区块链的上市公司评价方法及相关设备
CN118797338A (zh) 欺诈预测模型训练方法、装置、设备、存储介质及产品
US20230372812A1 (en) Method and apparatus for data synchronization, device and medium
CN115588515A (zh) 基于大数据的多级医疗协作系统及其方法
US11526375B2 (en) Systems and methods for pre-executing idiosyncratic computation through the application of algorithmic prediction of user behavior patterns

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 24846325

Country of ref document: EP

Kind code of ref document: A2