The aim of this study is to establish a deep learning model to automatically detect the presence and scoring of carotid plaques in neck CTA images, and to determine whether this model is compatible with manual interpretations.
Modeling CTA images for carotid artery segments with deep learning method and automatic carotid plaque presence and scoring will be useful and beneficial in clinical practice. The aim of this study is to establish a deep learning model to automatically detect the presence and scoring of carotid plaques in neck CTA images, and to determine whether this model is compatible with manual interpretations.
Study Type
OBSERVATIONAL
Enrollment
300
Istanbul MEdeniyet University Göztepe Prof. Dr. Süleyman Yalçın City Hospital
Kadıköy, Istanbul, Turkey (Türkiye)
RECRUITINGCorrelation of the machine learning model and manual interpretation
Evaluation of the correlation of the presence of plaque in the carotid segments with manual interpretation in the model obtained by machine learning method
Time frame: 1 day
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