Scopus
YÖKSİS Eşleşti
Future activity prediction of multiple sclerosis with 3D MRI using 3D discrete wavelet transform
Biomedical Signal Processing and Control · Eylül 2022
YÖKSİS Kayıtları
Future activity prediction of multiple sclerosis with 3D MRI using 3D discrete wavelet transform
Biomedical Signal Processing and Control · 2022 SCI-Expanded
DOKTOR ÖĞRETİM ÜYESİ ZÜLEYHA YILMAZ ACAR →
Future activity prediction of multiple sclerosis with 3D MRI using 3D discrete wavelet transform
Biomedical Signal Processing and Control · 2022 SCI-Expanded
PROFESÖR FATİH BAŞÇİFTÇİ →
Makale Bilgileri
DergiBiomedical Signal Processing and Control
Yayın TarihiEylül 2022
Cilt / Sayfa78
Scopus ID2-s2.0-85133525003
Özet
Multiple Sclerosis (MS) is a chronic and autoimmune neurological disease that is frequently seen especially in young people. MS lesions that can be seen with magnetic resonance imaging (MRI) findings are important biomarkers that provide information about the clinical prognosis and activity of the disease. The presence of new MS lesions is associated with future disease activity. This study aims to predict the future activity of MS using the 3D discrete wavelet transform (DWT) as a feature extraction method from 3D MRI. The 3D-DWT can be used as it provides spatial and spectral location features of MS lesions without losing their relationship between MRI slices. Ten different wavelet families of DWT are used individually, each of them is classified by six machine learning algorithms, and their feature extraction performances are compared. The highest F1-score, Precision, and Recall of 95.0% are obtained by the support vector machine algorithm on the SYM4, SYM8, and Haar wavelet families in the 3D MRI dataset consisting of 40 patients based on 5-fold cross validation. The results show that the 3D-DWT method is an effective method for feature extraction in predicting the future activity of MS.
Yazarlar (3)
1
Züleyha Yılmaz Acar
2
Fatih Başçiftçi
3
Ahmet Hakan Ekmekci
Anahtar Kelimeler
3D-DWT
3D MRI
Disease progression of Multiple Sclerosis
Future disease activity
Machine learning algorithms
Kurumlar
Selçuk Tip Fakültesi
Konya Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
4
Atıf
3
Yazar
5
Anahtar Kelime