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


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

CLINICAL RADIOLOGY, cilt.75, sa.5, ss.351-357, 2020 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Editöre Mektup
  • Cilt numarası: 75 Sayı: 5
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.crad.2019.12.008
  • Dergi Adı: CLINICAL RADIOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, CINAHL, EMBASE, MEDLINE
  • Sayfa Sayıları: ss.351-357
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Evet

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).