Medical object detection and identification via machine learning

Abstract

An approach for improving object detection performance by using bilateral organ information disclosed. The approach comprises introducing a penalty term to an object localization model. The penalty term encourages the model to identify same physical regions (actual same physical location in the patient's body) in multiple images, which create an image of the same organ. The approach includes a sub-component of the model that can output an entity embedding, in additional to the conventional classification and localization prediction. During optimization process, similar entity embedding for the same logical entity are encouraged, and similar entity embedding for different logical entities are discouraged.