Classification of Internal Carotid Artery Doppler Signals Using Hidden Markov Model and Wavelet Transform with Entropy

Basit Öğe Kaydı
dc.contributor.authorUğuz, Harun
dc.contributor.authorKodaz, Halife
dc.date.accessioned2020-03-26T17:47:26Z
dc.date.available2020-03-26T17:47:26Z
dc.date.issued2010
dc.departmentSelçuk Üniversitesien_US
dc.description4th International Conference on Advances in Information Technology (IAIT) -- NOV 04-05, 2010 -- Bangkok, THAILANDen_US
dc.description.abstractDoppler ultrasound has been usually preferred for investigation of the artery conditions in the last two decade, since it is a non-invasive method which is not risky. In this study, a biomedical system based on Discrete Hidden Markov Model (DHMM) has been developed in order to classify the internal carotid artery Doppler signals recorded from 191 subjects (136 of them had suffered from internal carotid artery stenosis and rest of them had been healthy subjects). Developed system comprises of three stages. In the first stage, for feature extraction, obtained Doppler signals were separated to its sub-bands using Discrete Wavelet Transform (DWT). In the second stage, entropy of each sub-band was calculated using Shannon entropy algorithm to reduce the dimensionality of the feature vectors via DWT. In the third stage, the reduced features of carotid artery Doppler signals were used as input patterns of the DHMM classifier. Our proposed method reached 97.38% classification accuracy with 5 fold cross validation (CV) technique. The classification results showed that purposed method is effective for classification of internal carotid artery Doppler signals.en_US
dc.description.sponsorshipKing Mongkuts Univ Technol Thonburi, Sch Informat Technolen_US
dc.identifier.citationUğuz, H., Kodaz, H., (2010). Classification of Internal Carotid Artery Doppler Signals Using Hidden Markov Model and Wavelet Transform with Entropy. Advances in Information Technology, (114), 183-191. Doi: 10.1007/978-3-642-16699-0_20
dc.identifier.endpage191en_US
dc.identifier.isbn978-3-642-16698-3
dc.identifier.issn1865-0929en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage183en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24696
dc.identifier.volume114en_US
dc.identifier.wosWOS:000288365600020en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorUğuz, Harun
dc.institutionauthorKodaz, Halife
dc.language.isoenen_US
dc.publisherSpringer-Verlag Berlinen_US
dc.relation.ispartofAdvances in Information Technologyen_US
dc.relation.ispartofseriesCommunications in Computer and Information Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectDiscrete Hidden Markov modelen_US
dc.subjectDoppler signalen_US
dc.subjectCarotid arteryen_US
dc.subjectWavelet Transformen_US
dc.subjectEntropyen_US
dc.titleClassification of Internal Carotid Artery Doppler Signals Using Hidden Markov Model and Wavelet Transform with Entropyen_US
dc.typeConference Objecten_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
4696.pdf
Boyut:
232.4 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale Dosyası
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Bilgisayar Mühendisliği Bölümü/Makale Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu