Atıf İçin Kopyala
SALİHOĞLU Y. S., Erdemir R. U., Puren B. A., ÖZDEMİR S., Uyulan C., ERGÜZEL T. T., ...Daha Fazla
MOLECULAR IMAGING AND RADIONUCLIDE THERAPY, cilt.31, sa.2, ss.82-88, 2022 (ESCI)
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Yayın Türü:
Makale / Tam Makale
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Cilt numarası:
31
Sayı:
2
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Basım Tarihi:
2022
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Doi Numarası:
10.4274/mirt.galenos.2021.43760
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Dergi Adı:
MOLECULAR IMAGING AND RADIONUCLIDE THERAPY
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Derginin Tarandığı İndeksler:
Emerging Sources Citation Index (ESCI), Scopus, TR DİZİN (ULAKBİM)
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Sayfa Sayıları:
ss.82-88
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Anahtar Kelimeler:
Solitary pulmonary nodule, PET/CT, radiomic, machine learning, LUNG-CANCER, TOMOGRAPHY
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Çanakkale Onsekiz Mart Üniversitesi Adresli:
Evet
Özet
Objectives: This study aimed to evaluate the ability of (18)fluorine-fluorodeoxyglucose (F-18-FDG) positron emission tomography/computed tomography (PET/CT) radiomic features combined with machine learning methods to distinguish between benign and malignant solitary pulmonary nodules (SPN).