Towards High-Quality Image Segmentation: Improving Topology Accuracy by Penalizing Neighbor Pixels

ArXi:2603.18671v1 Announce Type: new Standard deep learning models for image segmentation cannot guarantee topology accuracy, failing to preserve the correct number of connected components or structures. This, in turn, affects the quality of the segmentations and compromises the reliability of the subsequent quantification analyses. Previous works have proposed to enhance topology accuracy with specialized frameworks, architectures, and loss functions. However, these methods are often cumbersome to integrate into existing