AUTOMATIC INFERIOR VENA CAVA SEGMENTATION IN CONTRAST-ENHANCED CT VOLUMES

This paper presents a novel robust automatic method for the segmentation of the Inferior Vena Cava (IVC) in the proximity of the liver. In clinical diagnosis and surgery planning, IVC segmentation is essential since it strongly impacts both liver volumetry accuracy and vascularity analysis. Given the anatomical variability, the lack of clear boundaries and complexity of the surrounding structures along the IVC, its segmentation remains a difficult and open problem. To cope with such challenging conditions, we developed an implicit representation of a generalized cylinder and optimized a local region-based criterion under dedicated anatomical constraints. Our method was tested on a dataset of 20 contrast-enhanced CT scans, achieving 80% success rate in fully automatic mode. The remaining cases needed minimal user input (one point) to reach 95% success under radiology expert criteria.