Automatic inferior vena cava segmentation in contrast-enhanced CT volumes

Thierry Lefevre (1) , Benoît Mory (1) , Roberto Ardon (1) , Javier Sanchez-Castro (1) , Anthony Yezzi (2)

1 Medisys - MedisysResearch Lab
2 Georgia Institute of Technology [Atlanta]

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. (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

Domaines: Imagerie médicale; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Thierry Lefevre, Benoît Mory, Roberto Ardon, Javier Sanchez-Castro, Anthony Yezzi. Automatic inferior vena cava segmentation in contrast-enhanced CT volumes. 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Apr 2010, Rotterdam, Netherlands. pp.420-423, ⟨10.1109/ISBI.2010.5490321⟩. ⟨hal-00508788⟩