Centerline-Diameters Data Structure for Interactive Segmentation of Tube-Shaped Objects

Abstract

Interactive segmentation techniques are in high demand in medical imaging, where the user-machine interactions are to address the imperfections of a model and to speed up the manual annotation. All recently proposed interactive approaches have kept the segmentation mask at the core, an inefficient trait if complex elongated shapes, such as wires, catheters, or veins, need to be segmented. Herein, we propose a new data structure and the corresponding click encoding scheme for the interactive segmentation of such elongated objects, without the masks. Our data structure is based on the set of centerline and diameters, providing a good trade-off between the filament-free contouring and the pixel-wise accuracy of the prediction. Given a simple, intuitive, and interpretable setup, the new data structure can be readily integrated into existing interactive segmentation frameworks.