A Novel Approach for the Classification of Liver MR Images Using Complex Orthogonal Ripplet-II and Wavelet-Based Transforms
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER INTERNATIONAL PUBLISHING AG
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study presents a decision support system aid to radiologists for defining focal lesions and making diagnosis more accurate by using liver magnetic resonance images. A new method called the complex orthogonal Ripplet-II transform is proposed as a feature extraction procedure. Artificial neural network is utilized to classify the obtained features as a hemangioma or cyst. The results are evaluated with the results of the systems using Ridgelet, Ripplet type-II and orthogonal Ripplet type-II transforms. The highest accuracy ratio (85.3%) and area under curve value (0.92) are achived by the complex orthogonal Ripplet-II transform. The accuracy of the classification procedure is increased up to 95.6% by a combined system that collectively analyzes the results obtained from the artificial neural network outputs of the two methods (Ridgelet and complex orthogonal Ripplet-II transforms). While this combined system is built up of three methods (adding Ripplet type-II), the accuracy rate reaches 97.06% and the area under curve value to 0.99.
Açıklama
Anahtar Kelimeler
Artificial neural network, Biomedical image classification, Complex orthogonal Ripplet-II transform, Complex wavelet transform, Liver MR imaging, Ripplet type-II transform
Kaynak
CLASSIFICATION IN BIOAPPS: AUTOMATION OF DECISION MAKING
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
26
