Patent ID: 11941802
Assignee: ALIBABA GROUP HOLDING LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G  A | IPC A  G

Claim 16:
17. A method, comprising:
obtaining, by one or more processors, a target image from a target image source, the target image being obtained based at least in part on one or more inputs corresponding to a user selection;
receiving, by the one or more processors, a user selection pertaining to an image analysis process;
determining, by the one or more processors, a target image analysis process based at least in part on the user selection of the image analysis process;
analyzing, by the one or more processors, the target image based at least in part on an organ lesion segmentation model to identify a lesion comprised in a target object region in the target image, wherein the organ lesion segmentation model is selected based at least in part on an organ comprised in the target object region, and the organ lesion segmentation model is a machine learning model;
analyzing, by the one or more processors, a target object region comprised in the target image based at least in part on a disease recognition model to determine whether a patient associated with the target image has a disease or other abnormality, and classify any disease or abnormality afflicting the patient, wherein the organ lesion segmentation model is selected based at least in part on an organ comprised in the target object region; and
providing an image of the lesion and an indication of whether the patient has a particular disease or abnormality.