Abstract
Ankle fractures are common and, compared to other injuries, tend to be overlooked in the emergency department. We aim to develop a deep learning algorithm that can detect not only definite fractures but also obscure fractures. We collected the data of 1226 patients with suspected ankle fractures and performed both X-rays and CT scans. With anteroposterior (AP) and lateral ankle X-rays of 1040 patients with fractures and 186 normal patients, we developed a deep learning model. The training, validation, and test datasets were split in a 3/1/1 ratio. Data augmentation and under-sampling techniques were administered as part of the preprocessing. The Inception V3 model was utilized for the image classification. Performance of the model was validated using a confusion matrix and the area under the receiver operating characteristic curve (AUC-ROC). For the AP and lateral trials, the best accuracy and AUC values were 83%/0.91 in AP and 90%/0.95 in lateral. Additionally, the mean accuracy and AUC values were 83%/0.89 for the AP trials and 83%/0.9 for the lateral trials. The reliable dataset resulted in the CNN model providing higher accuracy than in past studies.
Highlights
Orthopedic radiography is one of the most common imaging methods to diagnose fractures
We reviewed the patients over 18 years of age with diagnosed ankle sprain or fracture and selected those who had undergone both
We manually labeled them, and the results are as follows: 1040 instances of patients were diagnosed with fractures, i.e., “abnormal” and 186 instances of those were without fractures, i.e., “normal”
Summary
Orthopedic radiography is one of the most common imaging methods to diagnose fractures. Fractures in the foot and ankle, tend to be overlooked or misdiagnosed when radiographs are interpreted especially in the emergency department (ED) [1]. Ankle injuries are a common cause for outpatient visits; it is important that their diagnosis be accurate for further evaluation and treatment. Artificial intelligence (AI) can potentially provide a solution to this challenge; several studies are presently being undertaken to detect fractures using deep learning technologies [4]. Deep learning is a subdomain of AI wherein a system is trained to imitate the human brain. Convolutional neural networks (CNN) is a widely used deep learning algorithm for data processing, especially for 2D images [5]
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