The invention relates to a hepatic
echinococcosis focus identification and classification method based on
deep learning. The method comprises the following steps: when a focus exists in a to-be-detected liver ultrasonic image, generating focus detection state information of each focus in the to-be-detected liver ultrasonic image, and for any focus, when the
pathological type of the focus is benign, performing coarse classification detection on the focus in a focus detection frame to generate coarse classification information of the focus; for any
lesion, when the coarse classification information of the
lesion is cystic hydatid type or vesicular hydatid type, determining that the
lesion is a hepatic
echinococcosis lesion, and performing hydatid
subdivision category detection and lesion
contour segmentation on the lesion to determine a corresponding hydatid
subdivision category when the lesion belongs to the cystic hydatid type or vesicular hydatid type, and if the lesion belongs to the vesicular hydatid type or vesicular hydatid type, determining that the lesion belongs to the hepatic
echinococcosis lesion. And a target contour of the lesion. According to the invention, the identification and classification of the hepatic echinococcosis can be effectively realized, and the precision and reliability of hepatic echinococcosis detection are improved.