Wrist Crack Classification Using Deep Learning and X-Ray Imaging
摘要
Wrist cracks are the most prevalent kind of crack and have a high incidence rate. Although wrist cracks are often identified with X-ray medical imaging, the portrayal of cracks may sometimes provide issues. Wrist cracks are common in humans’ wrist bones as a result of unintentional traumas like sliding. Many hospitals lack qualified specialists to identify wrist cracks. As a result, an automated method is necessary to lessen the strain on physicians while also identifying cracks. A CNN model for detecting wrist cracks obtained 0.98 accuracy, surpassing competitors, minimizing erroneous diagnoses and saving time in clinician assistance.