Table 1_A novel MRI-based deep learning–radiomics framework for evaluating cerebrospinal fluid signal in central nervous system infection.docx

Table 1_A novel MRI-based deep learning–radiomics framework for evaluating cerebrospinal fluid signal in central nervous system infection.docx

Introduction<p>Accurate and timely diagnosis of central nervous system infections (CNSIs) is critical, yet current gold-standard techniques like lumbar puncture (LP) remain invasive and prone to delay. This study proposes a novel noninvasive framework integrating handcrafted radiomic features...

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Auteur principal: Ferhat Cüce (22090151) (author)
Autres auteurs: Gökalp Tulum (22090154) (author), Muhammed Ikbal Isik (22090157) (author), Marziye Jalili (22090160) (author), Güven Girgin (22090163) (author), Ömer Karadaş (17071282) (author), Niray Baş (22090166) (author), Berza Özcan (22090169) (author), Ümit Savaşci (22090172) (author), Sena Şakir (22090175) (author), Akçay Övünç Karadaş (22090181) (author), Eda Teomete (22090184) (author), Onur Osman (8348769) (author), Jawad Rasheed (12370306) (author)
Publié: 2025
Sujets:
Foetal Development and Medicine
central nervous system infection
cerebrospinal fluid
brain MRI
Radiomics
deep learning
lumbar puncture
perivascular spaces
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