Age Estimation from Left-Hand Radiographs with Deep Learning Methods
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Int Information & Engineering Technology Assoc
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Bone age is estimated in pediatric medicine for medical and legal purposes. In pediatric medicine, it aids in the growth and development assessment of various diseases affecting children. In forensic medicine, it is required to determine criminal liability by age, refugee age estimation, and child-adult discrimination. In such cases, radiologists or forensic medicine specialists conduct bone age estimation from left hand-wrist radiographs using atlas methods that require time and effort. This study aims to develop a computer-based decision support system using a new modified deep learning approach to accelerate radiologists' workflow for pediatric bone age estimation from wrist radiographs. The KCRD dataset created by us was used to test the proposed method. The performance of the proposed modified IncepitonV3 model compared to IncepitonV3, MobileNetV2, EfficientNetB7 models. Acceptably high results (MAE=4.3, RMSE=5.76, and R-2=0.99) were observed with the modified IncepitonV3 transfer deep learning method.
Açıklama
Anahtar Kelimeler
bone age estimation, CNN, computer-aided diagnosis, deep learning
Kaynak
Traitement Du Signal
WoS Q Değeri
Q3
Scopus Q Değeri
N/A
Cilt
38
Sayı
6
