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An iris based lungs pre-diagnostic system

dc.contributor.authorHussain, Tassadaq
dc.contributor.authorHaider, Amna
dc.contributor.authorMuhammad, Abdul Malik
dc.contributor.authorAgha, Areeb
dc.contributor.authorKhan, Bilal
dc.contributor.authorRashid, Fawad
dc.contributor.authorRaza, Muhammad Saad
dc.contributor.authorDin, Moainud
dc.contributor.authorKhan, Mehran
dc.contributor.authorUllah, Sami
dc.contributor.authorAhmed, Abdelmalik Taleb
dc.contributor.authorAyguadé Parra, Eduard
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2020-10-15T09:39:09Z
dc.date.available2020-10-15T09:39:09Z
dc.date.issued2019
dc.identifier.citationHussain, T. [et al.]. An iris based lungs pre-diagnostic system. A: International Conference on Computing, Mathematics and Engineering Technologies. "2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 1-5. ISBN 978-1-5386-9509-8. DOI 10.1109/ICOMET.2019.8673495.
dc.identifier.isbn978-1-5386-9509-8
dc.identifier.urihttp://hdl.handle.net/2117/330287
dc.description© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractHuman lungs are essential respiratory organs. Different Obstructive Lung Diseases (OLD) such as bronchitis, asthma, lungs cancer etc. affects the respiration. Diagnosing OLD in the initial stage is better than diagnosing and curing them later. The delay in diagnosing OLD is due to expensive diagnosing tool and experts requirement. Therefore, a non-invasive diagnosing tool for OLD is required that identifies dysfunctional lungs without the support of expert, complex and expensive diagnosing types of equipment. In this work, we design an Iris based Lungs Pre-diagnostic System (ILPS). The ILPS takes iris images as input and identifies dysfunctional Lungs based on iridology map. While testing with 50 lungs patients, the results confirm that the ILPS identifies dysfunctional lungs patients with the accuracy of 88%.
dc.description.sponsorshipThe research leading to these results has received funding from the Higher Education Commission under NRPU 2017/18.
dc.format.extent5 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subject.lcshDiagnostic imaging
dc.subject.lcshLungs -- Diseases, Obstructive
dc.subject.lcshIris (Eye) -- Examination
dc.subject.otherIridology
dc.subject.otherHealth-care
dc.subject.otherEmbedded computer vision
dc.subject.otherArtificial intelligence
dc.titleAn iris based lungs pre-diagnostic system
dc.typeConference report
dc.subject.lemacDiagnòstic per la imatge
dc.subject.lemacPulmons -- Malalties obstructives
dc.subject.lemacIris (Ull) -- Examen
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1109/ICOMET.2019.8673495
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8673495
dc.rights.accessOpen Access
local.identifier.drac27852227
dc.description.versionPostprint (author's final draft)
local.citation.authorHussain, T.; Haider, A.; Muhammad, A.; Agha , A.; Khan, B.; Rashid, F.; Raza, M.; Din, M.; Khan, M.; Ullah, S.; Ahmed, A.; Ayguadé, E.
local.citation.contributorInternational Conference on Computing, Mathematics and Engineering Technologies
local.citation.publicationName2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)
local.citation.startingPage1
local.citation.endingPage5


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