Systems and methods for processing electronic images to detect contamination in specimen preparations

This invention describes a computer system that analyzes digital images of tissue specimens to find external contaminants, often called "floaters." The system, referred to as a "floater detection platform," uses machine learning models like Mask R-CNN or U-Net, trained on many images, to identify regions that might contain these unwanted particles. Based on what the machine learning predicts, the system decides if a specific image region needs further processing to confirm the contamination.