In the treatment of acute infarction, the detection of abnormal high signals in diffusion weighted images contributes to early diagnosis and treatment of infarction. In this study, we developed a deep learning neural network model via autoencoder (AE) to diagnosis brain infarction and predict vascular territory automatically from a DWI image. 1582 brain images including normal and abnormal brain which had infarctions were used as a training and test dataset. As a result, our model detected brain infarction and estimated vascular territory with high accuracy. It can be an effective indicator for diagnosing correctly infarction and predicting treatment effect.