Trexplorer Super: Topologically Correct Centerline Tree Tracking of Tubular Objects in CT Volumes

Tubular tree structures, such as blood vessels and airways, are essential in human anatomy, and accurately tracking them while preserving their topology is crucial for various downstream tasks. Trexplorer is a recurrent model designed for centerline tracking in 3D medical images, but it is prone to predicting duplicate branches and terminating tracking prematurely. To address these issues, we present Trexplorer Super, an enhanced version that substantially improves performance through several novel advancements. Evaluating centerline tracking models is challenging due to the lack of public benchmark datasets. To enable thorough evaluation, we develop three centerline datasets, one synthetic and two real, each with increasing difficulty. Using these datasets, we perform a comprehensive comparison of existing state-of-the-art (SOTA) models with our approach. Trexplorer Super outperforms previous SOTA models on every dataset. Our results also highlight that strong performance on synthetic data does not necessarily translate to real datasets.

In International Conference on Medical Image Computing and Computer-Assisted Intervention