Disclosed is a cerebral hemorrhage amount calculation method based on deep learning. The specific steps are: S1: acquiring cerebral hemorrhage CT image data and marking same; S2: designing a segmentation model of a cerebral hemorrhage area that is based on deep learning, and training the segmentation model by using the marked cerebral hemorrhage CT image data; S3: inputting test cerebral hemorrhage CT image data into the trained segmentation model to obtain a segmentation result; S4: calculating a cerebral hemorrhage volume according to the obtained segmentation result; and S5: generating a structured report including a cerebral hemorrhage position and the cerebral hemorrhage volume. By means of the method, the amount of cerebral hemorrhage can be calculated accurately and quickly, providing important decision-making information for clinical intervention.
CEREBRAL HEMORRHAGE AMOUNT CALCULATION METHOD BASED ON DEEP LEARNING