The diagnostic value of quantitative texture analysis of conventional MRI sequences using artificial neural networks in grading gliomas


Alis D., Bagcilar O., Senli Y. D. , İŞLER C. , Yergin M., Kocer N., ...Daha Fazla

CLINICAL RADIOLOGY, cilt.75, ss.351-357, 2020 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 75 Konu: 5
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.crad.2019.12.008
  • Dergi Adı: CLINICAL RADIOLOGY
  • Sayfa Sayıları: ss.351-357

Özet

AIM: To explore the value of quantitative texture analysis of conventional magnetic resonance imaging (MRI) sequences using artificial neural networks (ANN) for the differentiation of high-grade gliomas (HGG) and low-grade gliomas (LGG).