Image-based detection of object condition

A system for image-based detection an object internal to a patient, the system comprising:

• a database configured to store a trained model for an object internal to a patient, the trained model being generated from one or more machine learning algorithms that are trained on training images with annotated information identifying the object, wherein the trained model is configured to be used to detect the object from unannotated images;
• an imaging computer system that is configured to:
• receive, from an imaging device, one or more images of the object internal to the patient, wherein the imaging device is configured to capture the one or more images of the object from a position external to the patient,
• access the trained model for the object from the database,
• detecting, based on applying the trained model to the one or more images of the object, the object internal to the patient from the one or more images, and
• provide information identifying the object internal to the patient;
• and
• a display to monitor the object internal to the patient, the display being configured to output (i) the one or more images of the object as captured by the imaging device from the position external to the patient, and (ii) the information identifying the object internal to the patient as determined based on application of the trained model to the one or more images.

A method for image-based detection an object internal to a patient, the method comprising:

• receiving, from an imaging device, one or more images of the object internal to the patient, wherein the imaging device is configured to capture the one or more images of the object from a position external to the patient;
• accessing a trained model for the object from a database, wherein the trained model is stored in the database and generated from one or more machine learning algorithms trained on training images of the object with annotated information identifying the object, wherein the trained model is configured to be used to detect the object from unannotated images;
• detecting, based on applying the trained model to the one or more images of the object, the object internal to the patient;
• and
• providing the information identifying the object for presentation on a display, the display being configured to output (i) the one or more images of the object as captured by the imaging device, and (ii) the information identifying of the object internal to the patient as determined based on application of the trained model to the one or more images.

A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving, from an imaging device, one or more images of the object internal to the patient, wherein the imaging device is configured to capture the one or more images of the object from a position external to the patient;
• accessing a trained model for the object from a database, wherein the trained model is stored in the database and generated from one or more machine learning algorithms trained on training images of the object with annotated information identifying the object, wherein the trained model is configured to be used to detect the object from unannotated images;
• detecting, based on applying the trained model to the one or more images of the object, the object internal to the patient;
• and
• providing the information identifying the object for presentation on a display, the display being configured to output (i) the one or more images of the object as captured by the imaging device, and (ii) the information identifying of the object internal to the patient as determined based on application of the trained model to the one or more images.