Patientspecific model of brain deformation Application to medical image registration.docx
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PatientspecificmodelofbraindeformationApplicationtomedicalimageregistration
DevelopmentofanHL7interfaceengine,basedontreestructureandstreamingalgorithm,forlarge-sizemessageswhichincludeimagedata OriginalResearchArticle
ComputerMethodsandProgramsinBiomedicine
AbasicassumptionofHealthLevelSeven(HL7)protocolis‘Nolimitationofmessagelength’.However,mostexistingcommercialHL7interfaceenginesdolimitmessagelengthbecausetheyusethestringarraymethod,whichisruninthemainmemoryfortheHL7messageparsingprocess.Specifically,messageswithimageandmulti-mediadatacreatealongstringarrayandthuscausethecomputersystemtoraisecriticalandfatalproblem.Consequently,HL7messagescannothandletheimageandmulti-mediadatanecessaryinmodernmedicalrecords.
Thisstudyaimstosolvethisproblemwiththe‘streamingalgorithm’method.ThisnewmethodforHL7messageparsingappliesthecharacter-streamobjectwhichprocesscharacterbycharacterbetweenthemainmemoryandharddiskdevicewiththeconsequencethattheprocessingloadonmainmemorycouldbealleviated.Themainfunctionsofthisnewenginearegenerating,parsing,validating,browsing,sending,andreceivingHL7messages.Also,theenginecanparseandgenerateXML-formattedHL7messages.
ThisnewHL7enginesuccessfullyexchangedHL7messageswith10 megabytesizeimagesanddischargesummaryinformationbetweentwouniversityhospitals.
ArticleOutline
1.Introductionandbackground
2.Designconsiderations
2.1.Developingenvironment
2.2.Algorithmandconceptdesigns
2.2.1.Treestructure
2.2.2.Streamingparsingalgorithm
2.2.3.BinarydatatransformingforinsertingintoanHL7message
2.2.4.Validatingalgorithm
2.2.4.1.Syntaxcheckonsegmentlevel
2.2.4.2.Syntaxcheckingforrequiredfields
2.2.4.3.Validatingfordatavalueofeachnode
2.2.4.4.Processforerrorsorexceptions
2.2.5.Addressingmethodforpointingouteachnode
3.Systemdescription
3.1.Systemdesign
3.1.1.Classflowdiagram
3.1.2.Classblockdiagram
3.1.3.ElementNodeclass
3.1.4.HL7MessageTreeclass
3.1.4.1.Constructor
3.1.4.2.Problemsolutionofvariabledatatype
3.1.4.3.Automaticdatatransforming
3.2.Implementation
3.3.Test
3.4.Experimentalapplicationforperformanceevaluation
4.Statusreport
4.1.Performanceevaluation
4.1.1.Messagesendingandreceiving
4.1.2.Messageparsing
4.1.3.Messagegenerating
4.1.4.Messagevalidating
4.1.5.Menagebrowsing
4.1.6.Encodinganddecodingfunctionforimagedata
5.Lessonslearnedandfutureplans
5.1.EDorRPdatatypeasamethodofmultimediadatatransferring
5.2.Futureplans
5.3.Summary
Acknowledgements
References
Multi-pathselectionformultipledescriptionvideostreamingoveroverlaynetworks OriginalResearchArticle
SignalProcessing:
ImageCommunication
Real-timemediadistributionovertheInternetposesseveralchallengingproblemsduetoitsstringentdelay/lossrequirementsandcomplexnetworkdynamics.Apromisingapproachtoalleviatethesevereimpactsofthesedynamicsistotransmitthemediaoverdiversepaths.Forsuchanenvironment,multipledescription(MD)codinghasbeenpreviouslyproposedtoproducemultipleindependentlydecodablestreamsthatareroutedoverpartiallylink–disjoint(non-shared)pathsforcombattingburstypacketlossesanderrorpropagation.However,selectingthesepathsappropriatelyisfundamentaltothesuccessofMDstreamingandpathdiversity.Hence,inthispaperwedevelopmodelsforMDstreamingovermultiplepathsandbasedonthesemodelsweproposeamulti-pathselectionmethodthatchoosesasetofpathsmaximizingtheoverallqualityattheclientundervariousconstraints.ThesimulationresultswithMPEG-2showthatsizeableaveragepeaksignal-to-noiseratio(PSNR)improvements(rangingfrom0.73to6.07 dB)canbeachievedwhenthesourcevideoisstreamedoverintelligentlyselectedmultiplepathsasopposedtoovertheshortestpathormaximallylink–disjointpaths.InadditiontothePSNRimprovement,end-usersexperienceamorecontinual,i.e.,uninterrupted,streamingquality.Ourworkalsoconsidersthearchitectureandmechanismsbywhichmulti-pathstreamingcanbeaccomplishedoveraconventionalIPnetwork.
ArticleOutline
1.Introduction
2.Backgroundonmultipledescriptioncoding
3.Envisionednetworkmodel
3.1.Overlaymodel
3.2.Definitions
3.3.Linkparameters
4.Multi-pathselection
4.1.Bandwidth-distortionrelation
4.2.Computationofsuccessprobabilities
4.2.1.Arrivalprobability
4.2.1.1.Preliminaries
4.2.1.2.Pathsegregation
4.2.1.3.Linkaggregation
4.2.2.On-timedeliveryprobability
4.3.End-to-endmulti-pathmodel
5.Simulationresults
5.1.Methodology
5.2.Single-hoptopology
5.3.Internettopology
5.4.Discussion
6.Conclusions
Acknowledgements
References
Videostreaming:
Implementationandevaluationinanundergraduatenursingprogram OriginalResearchArticle
NurseEducationToday
Videostreamingtechnologyenablesvideocontent,heldonthewebsites,tobestreamedviatheweb.WereporttheimplementationandevaluationofvideostreaminginanundergraduatenursingprograminametropolitanuniversityinAustralia.Students(n = 703)wereemailedasurveywitha15%responserate.Wefoundthat91%(n = 74)ofrespondentsstatedthatvideostreamingassistedtheirlearning.Forty-sixpercent(n = 50)ofstudentshaddifficultyaccessingvideostreaming(particularlyatthebeginningofthestudyperiod).Overa97-dayperiodtherewere8440“hits”tothesitefrom1039differentinternetprotocol(IP)addresses.Therewere4475videostreamingsessionsundertakenbyusers.Videostreamingwasusedforreviewingpreviouslyattendedlectures(52%,n = 56),examinationpreparation(34%,n = 37),viewingmissedlectures(27%,n = 29)andclasspreparation(9%,n = 10).Ourexperiencewiththeintroductionofvideostreaminghasmetwithgeneralenthusiasmfrombothstudentsandteachingstaff.Videostreaminghasparticularrelevanceforruralstudents.
ArticleOutline
Introduction
Background
Development
Implementation
Informationsessions
Evaluation
Websiteusage
Studentevaluation
Lecturerevaluation
Examinationresults
Discussion
Conclusion
Acknowledgements
References
Adoptingelectronicmedicalrecordsinprimarycare:
Lessonslearnedfromhealthinformationsystemsimplementationexperienceinsevencountries OriginalResearchArticle
InternationalJournalofMedicalInformatics
Theadoptionofhealthinformationsystemsisseenworldwideasonemethodtomitigatethewideninghealthcaredemandandsupplygap.Thepurposeofthisreviewwastoidentifythecurrentstateofknowledgeabouthealthinformationsystemsadoptioninprimarycare.Thegoalwastounderstandfactorsandinfluencersaffectingimplementationoutcomesfromprevioushealthinformationsystemsimplementationsexperiences.Acomprehensivesystematicliteraturereviewofpeerreviewedandgreyliteraturewasundertakentoidentifythecurrentstateofknowledgeregardingtheimplementationofhealthinformationsystems.Atotalof6databases,27journalwebsites,20websitesfromgreysources,9websitesfrommedicalcollegesandprofessionalassociationsaswellas22government/commissionwebsitesweresearched.Thesearchesreturnedalmost3700articletitles.Eighty-sixarticlesmetourinclusionandexclusioncriteria.
Articlesshowthatsystems’graphicaluserinterfacedesignquality,featurefunctionality,projectmanagement,procurementandusers’previousexperienceaffectimplementationoutcomes.Implementershadconcernsaboutfactorssuchasprivacy,patientsafety,provider/patientrelations,staffanxiety,timefactors,qualityofcare,finances,efficiency,andliability.Thereviewshowedthatimplementerscaninsulatetheprojectfromsuchconcernsbyestablishingstrongleadership,usingprojectmanagementtechniques,establishingstandardsandtrainingtheirstafftoensuresuchrisksdonotcompromiseimplementationsuccess.Thereviewrevealedtheconceptofsocio-technicalfactors,or“fit”factors,thatcomplicatehealthinformationsystemsdeployment.Thesocio-technicalperspectiveconsidershowthetechnicalfeaturesofahealthinformationsysteminteractwiththesocialfeaturesofahealthcareworkenvironment.
Thereviewshowedthatqualityofcare,patientsafetyandprovider/patientrelationswerenot,positivelyornegatively,affectedbysystemsimplementation.Thefactthatnoarticleswerefoundreviewingthebenefitsordrawbacksofhealthinformationsystemsaccruingtopatientsshouldbeconcerntoadopters,payersandjurisdictions.Nostudieswerefoundthatcomparedhowprovider–patientinteractionsininterviewsareeffectedwhenprovidersusedelectronichealthinformationsystemsasopposedtothepaperequivalent.Verylittleinformationwasavailableaboutprivacyandliability.
ArticleOutline
1.Introduction
1.1.Background
1.2.Objectives
2.Methodology
3.Results
4.Discussion
5.Strengths&weaknesses
6.Conclusions
Acknowledgements
References
PlayingforReal:
VideoGamesandStoriesforHealth-RelatedBehaviorChange ReviewArticle
AmericanJournalofPreventiveMedicine
Background
Videogamesprovideextensiveplayerinvolvementforlargenumbersofchildrenandadults,andtherebyprovideachannelfordeliveringhealthbehaviorchangeexperiencesandmessagesinanengagingandentertainingformat.
Method
Twenty-sevenarticleswereidentifiedon25videogamesthatpromotedhealth-relatedbehaviorchangethroughDecember2006.
Results
Mostofthearticlesdemonstratedpositivehealth-relatedchangesfromplayingthevideogames.Variabilityinwhatwa