深度学习工具有助于检测和分割 X 光图像中的异常
以往寻找放射 X 光片、超声和核磁共振中的生物异常需要人类检查员发挥灵活性。现在，深度学习式缺陷探测和分割工具可以快速准确地识别医学图像中的异常。无论是寻找特定的异常还是偏离身体正常外观的地方，Cognex Deep Learning 都能将人工检查员的灵活性与计算机化系统的速度和稳健性结合。
The defect detection tool can be used to inspect a medical X-ray image or detect defects on an ultrasonic image simply by learning the normal appearance of an object, including its significant but tolerable variations. The defect detection tool develops a reference model of an organ’s normal appearance, as well as specific types of anomalies, based on training on a set of sample images. Any anomalies which digress from the normal physiology of the targeted zone are flagged as defects for a CAD computer-aided diagnosis by an expert radiologist.