Automated Data Adaptation for the Segmentation of Blood Vessels

This paper addresses domain shifts in image analysis for diagnostics, causing compatibility issues with AI models for segmentation. Two approaches are presented: one using heuristic optimization to adapt input images through selected algorithms and parameter optimization, and the other employing an additional neural network for dataset recoloring based on segmentation quality. Both methods significantly enhance segmentation quality without altering the model, showing promise in improving diagnostic accuracy and patient care in medical image analysis.