Rad Rounds September 2017: Bone Age Assessment with Artificial Intelligence

In a Journal of Digital Imaging paper published online in March 2017, researchers at Massachusetts General Hospital described a deep learning system for bone age assessment that addresses this limitation and provides a fully automated approach for clinical implementation. Here, AI infers the bone age from an X-ray image with no other patient information, trained by a convolutional neural network (CNN) using a data set including age and associated ideal X-rays. A CNN is a class of deep learning networks that mimics the neural connectivity patterns found in the animal visual cortex. It can provide confidence level and predicted age for any X-ray within seconds. The researchers tested the new deep learning system by applying it to more than 10,000 radiographs obtained at Mass General between 2005 and 2015.