Systems and methods for analysis of medical images for scoring of inflammatory bowel disease

A system for treatment of inflammatory bowel disease (IBD) in a patient and determining a score of disease activity, the system comprising:

• one or more processing devices;
• and
• a memory storing instructions that, when executed by the one or more processing devices, cause the one or more processing devices to perform operations comprising:
• obtaining image data including endoscopic images of a gastrointestinal tract (GI) of a patient,
• determining one or more features to extract from the image data, the features each representing a physical parameter of the GI tract;
• extracting the one or more features from the image data to form a feature vector;
• selecting a machine learning model based on the one or more features included in the feature vector;
• processing the feature vector using the machine learning model, the machine learning model being trained with labeled image data representing instances of symptoms of IBD being in the GI tract, the labeled image data associating scores representing a severity of IBD the respective instances of the symptoms;
• determining, based on the processing, a score representing a severity of IBD in the patient indicated by the image data;
• and
• storing, in a data store, the score in association with the image data.

One or more non-transitory computer readable media storing instructions for treatment of inflammatory bowel disease (IBD) in a patient and determining a score of disease activity, wherein the instructions, when executed by one or more processing devices, cause the one or more processing devices to perform operations comprising:

• obtaining image data including endoscopic images of a gastrointestinal tract (GI) of a patient;
• determining one or more features to extract from the image data, the features each representing a physical parameter of the GI tract;
• extracting the one or more features from the image data to form a feature vector;
• selecting a machine learning model based on the one or more features included in the feature vector;
• processing the feature vector using the machine learning model, the machine learning model being trained with labeled image data representing instances of symptoms of IBD being in the GI tract, the labeled image data associating scores representing a severity of IBD the respective instances of the symptoms;
• determining, based on the processing, a score representing a severity of IBD in the patient indicated by the image data;
• and
• storing, in a data store, the score in association with the image data.