Diagnosis of head CT image by on-premise deep learning

Abstract

We studied whether cerebral hemorrhage can be diagnosed correctly by deep learning with convolutional neural network using CT images taken at our hospital. Data processing techniques such as trimming-off and augmentation improved the precision rate of image classification. Generally, a large amount of image data is required for deep leaning. However, it is often difficult to collect many cases in one hospital. Our results suggest the possibility of on-premise medical image recognition with deep learning in the future.