Techniques of medical image processing and analysis accelerated by high-performance computing: a systematic literature review

dc.contributor.authorGulo, Carlos A. S. J.
dc.contributor.authorSementille, Antonio C. [UNESP]
dc.contributor.authorTavares, João Manuel R. S.
dc.contributor.institutionResearch Group PIXEL - UNEMAT
dc.contributor.institutionUniversidade do Porto
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T16:50:34Z
dc.date.available2018-12-11T16:50:34Z
dc.date.issued2017-11-16
dc.description.abstractTechniques of medical image processing and analysis play a crucial role in many clinical scenarios, including in diagnosis and treatment planning. However, immense quantities of data and high complexity of the algorithms often used are computationally demanding. As a result, there now exists a wide range of techniques of medical image processing and analysis that require the application of high-performance computing solutions in order to reduce the required runtime. The main purpose of this review is to provide a comprehensive reference source of techniques of medical image processing and analysis that have been accelerated by high-performance computing solutions. With this in mind, the articles available in the Scopus and Web of Science electronic repositories were searched. Subsequently, the most relevant articles found were individually analyzed in order to identify: (a) the metrics used to evaluate computing performance, (b) the high-performance computing solution used, (c) the parallel design adopted, and (d) the task of medical image processing and analysis involved. Hence, the techniques of medical image processing and analysis found were identified, reviewed, and discussed, particularly in terms of computational performance. Consequently, the techniques reviewed herein present the progress made so far in reducing the computational runtime involved, and the difficulties and challenges that remain to be overcome.en
dc.description.affiliationCNPq National Scientific and Technological Development Council Research Group PIXEL - UNEMAT
dc.description.affiliationPrograma Doutoral em Engenharia Informática Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial Faculdade de Engenharia Universidade do Porto
dc.description.affiliationDepartamento de Ciências da Computação Faculdade de Ciências Universidade Estadual Paulista-UNESP
dc.description.affiliationInstituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial Departamento de Engenharia Mecânica Faculdade de Engenharia Universidade do Porto
dc.description.affiliationUnespDepartamento de Ciências da Computação Faculdade de Ciências Universidade Estadual Paulista-UNESP
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.format.extent1-18
dc.identifierhttp://dx.doi.org/10.1007/s11554-017-0734-z
dc.identifier.citationJournal of Real-Time Image Processing, p. 1-18.
dc.identifier.doi10.1007/s11554-017-0734-z
dc.identifier.file2-s2.0-85034226092.pdf
dc.identifier.issn1861-8200
dc.identifier.scopus2-s2.0-85034226092
dc.identifier.urihttp://hdl.handle.net/11449/170382
dc.language.isoeng
dc.relation.ispartofJournal of Real-Time Image Processing
dc.relation.ispartofsjr0,322
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectImage reconstruction
dc.subjectImage registration
dc.subjectImage segmentation
dc.subjectMedical imaging
dc.titleTechniques of medical image processing and analysis accelerated by high-performance computing: a systematic literature reviewen
dc.typeArtigo
unesp.author.lattes1882712230914196[2]
unesp.author.orcid0000-0002-4337-514X[2]

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