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dc.contributor.authorAssis, Wânderson de Oliveira
dc.contributor.authorCoelho, Alessandra Dutra
dc.contributor.authorSantos, Jonatan Marques dos
dc.contributor.authorPalauro, Pedro Henrique
dc.contributor.authorCisneros Filho, Cesar Abraham Flores
dc.contributor.authorSilva, Danilo Argollo Pirutti
dc.contributor.authorFioretti, Alexandre Cesar
dc.contributor.authorCardelino, Bruno Oliveira
dc.contributor.authorMiranda, Robson Barbosa de
dc.date.accessioned2024-10-11T16:24:42Z
dc.date.available2024-10-11T16:24:42Z
dc.date.issued2022
dc.identifier.citationInt. Conf. Technol., Learn. Teach. Electron., TAEE - Proc.
dc.identifier.isbn978-166542161-4
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85137118001&doi=10.1109%2fTAEE54169.2022.9840688&partnerID=40&md5=74370f4555612aa6896cb27b69816c41
dc.identifier.urihttps://repositorio.maua.br/handle/MAUA/726
dc.description.abstractThis work presents a case study in the field of medicine employing digital image processing and artificial intelligence techniques based on artificial neural networks. The application consists on the development of a software for the treatment of images captured in vascular ultrasound exams with color Doppler in order to diagnose carotid percentage occlusion (carotid stenosis). The developed application can be used as a tool for engineering education, allowing the use and evaluation of several image processing techniques in engineering, such as character recognition, color identification, filtering and contour detection, among other techniques. Additionally, it allows the integration of neural network concepts for data processing. © 2022 IEEE.en
dc.languageInglêspt_BR
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en
dc.relation.ispartof15th International Conference of Technology, Learning and Teaching of Electronics, TAEE 2022 - Proceedings
dc.relation.haspart15th International Conference of Technology, Learning and Teaching of Electronics, TAEE 2022
dc.rightsAcesso Restrito
dc.sourceScopusen
dc.subjectdoppler vascular ultrasonographyen
dc.subjectengineering educationen
dc.subjectImage processingen
dc.subjectneural networksen
dc.subjectApplication programsen
dc.subjectCharacter recognitionen
dc.subjectData handlingen
dc.subjectEngineering educationen
dc.subjectImage processingen
dc.subjectUltrasonic applicationsen
dc.subjectArtificial intelligence techniquesen
dc.subjectCarotid stenosisen
dc.subjectCase-studiesen
dc.subjectColor Doppleren
dc.subjectDeveloped applicationsen
dc.subjectDopple vascular ultrasonographyen
dc.subjectDoppleren
dc.subjectImages processingen
dc.subjectNeural-networksen
dc.subjectVascular ultrasounden
dc.subjectNeural networksen
dc.titleTeaching image processing and artificial neural networks in engineering - A case study in medicineen
dc.typeTrabalho apresentado em eventopt_BR
dc.identifier.doi10.1109/TAEE54169.2022.9840688
dc.description.affiliationInstituto Mauá de Tecnologia, Electronics Engineering, São Caetano do Sul, Sp, Brazil
dc.description.affiliationVascular Surgery and Sonography, Faculdade de Medicina Do Abc, Santo André, SP, Brazil
dc.description.affiliationVascular Surgery, Faculdade de Medicina Do Abc, Santo André, SP, Brazil
dc.description.affiliationVascular Surgery and Sonography, Faculdade de Ciências Médicas da Santa Casa de S. P., São Paulo, SP, Brazil
dc.identifier.scopus2-s2.0-85137118001pt_BR


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