Výsledky vyhledávání - "Amalya Zeynalova"

Diagnostic value of contrast-enhanced vessel wall imaging in the evaluation of various intracranial non-vascular pathologies: a single center experience

Autor: Amalya Zeynalova

Publikováno v: Haydarpasa Numune Training and Research Hospital Medical Journal.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::036aa8d1630071b1aa2fd75699e8a18d
https://doi.org/10.14744/hnhj.2022.71542

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Radiogenomics of lower-grade gliomas: machine learning–based MRI texture analysis for predicting 1p/19q codeletion status

Autor: Ozgur Kilickesmez, Saime Turgut Gunes, Amalya Zeynalova, Ipek Sel, Burak Kocak, Ozlem Korkmaz Kaya, Emine Sebnem Durmaz, Ece Ates

Publikováno v: European Radiology. 30:877-886

To evaluate the potential value of the machine learning (ML)-based MRI texture analysis for predicting 1p/19q codeletion status of lower-grade gliomas (LGG), using various state-of-the-art ML algorithms.For this retrospective study, 107 patients with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1419990f5b6bc9d5cb898edafbc7f33c
https://doi.org/10.1007/s00330-019-06492-2

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Evaluation of sporadic intracranial cavernous malformations for detecting associated developmental venous anomalies: added diagnostic value of C-arm contrast-enhanced cone-beam CT to routine contrast-enhanced MRI

Autor: Burak Kocak, Amalya Zeynalova, Osman Kizilkilic, Bora Korkmazer, Civan Islak, Naci Kocer

Publikováno v: European Radiology. 29:783-791

Our purpose was to investigate the added diagnostic value of C-arm contrast-enhanced cone-beam CT (CE-CBCT) to routine contrast-enhanced MRI (CE-MRI) in detecting associated developmental venous anomalies (DVAs) in patients with sporadic intracranial

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a725b45fb2f2f8364dcf0d777f13fee
https://doi.org/10.1007/s00330-018-5652-3

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Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI

Autor: Okan Turk, Osman Kizilkilic, Burak Kocak, Emine Sebnem Durmaz, Amalya Zeynalova, Nil Comunoglu, Necmettin Tanriover, Civan Islak, Naci Kocer, Gamze Ozcan, Kerem Ozcan

Publikováno v: Neuroradiology. 61(7)

To evaluate the potential value of machine learning (ML)-based histogram analysis (or first-order texture analysis) on T2-weighted magnetic resonance imaging (MRI) for predicting consistency of pituitary macroadenomas (PMA) and to compare it with tha

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a3e902e30f5df4ff815ed60c3383343
https://pubmed.ncbi.nlm.nih.gov/31011772

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