Enhanced enchondroma detection from x-ray images using deep learning: A step towards accurate and cost-effective diagnosis
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
John Wiley and Sons Inc
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This study investigates the automated detection of enchondromas, benign cartilage tumors, from x-ray images using deep learning techniques. Enchondromas pose diagnostic challenges due to their potential for malignant transformation and overlapping radiographic features with other conditions. Leveraging a data set comprising 1645 x-ray images from 1173 patients, a deep-learning model implemented with Detectron2 achieved an accuracy of 0.9899 in detecting enchondromas. The study employed rigorous validation processes and compared its findings with the existing literature, highlighting the superior performance of the deep learning approach. Results indicate the potential of machine learning in improving diagnostic accuracy and reducing healthcare costs associated with advanced imaging modalities. The study underscores the significance of early and accurate detection of enchondromas for effective patient management and suggests avenues for further research in musculoskeletal tumor detection. © 2024 The Author(s). Journal of Orthopaedic Research® published by Wiley Periodicals LLC on behalf of Orthopaedic Research Society.
Açıklama
Anahtar Kelimeler
deep learning, Detectron2, enchondromas, machine learning, x-ray
Kaynak
Journal of Orthopaedic Research
WoS Q Değeri
Scopus Q Değeri
Q2
