基于YOLOv5的肺炎CT检测

CT Detection of Pneumonia Based on YOLOv5

神经网络的发展让计算机模拟人类大脑神经元来解释图像,可以准确且迅速地识别图像内容,因此,通过计算机辅助医疗诊断的技术具有一定研究意义。将肺炎CT的检测作为目标检测的分类问题进行考虑,通过YOLOv5提取肺炎CT医学影像的特征,判断患者是否患有肺炎,可以减少医护人员的工作量。最后得到的模型检测效果较好,可以在一定程度上辅助医生诊断。

The development of neural networks enables computers to simulate human brain neurons to interpret images and identify image content accurately and quickly.Therefore,the technology of computer-aided medical diagnosis has certain research significance.Considering the detection of pneumonia CT as the classification of target detection,can extract the characteristics of pneumonia CT medical images through yolov5 to determine whether the patient has pneumonia,which can reduce the work of medical staff.Finally,the model detection effect is good,which can help doctors diagnose to a certain extent.