Trexplorer: Recurrent DETR for Topologically Correct Tree Centerline Tracking
Paper in proceeding, 2024

Tubular structures with tree topology such as blood vessels, lung airways, and more are abundant in human anatomy. Tracking these structures with correct topology is crucial for many downstream tasks that help in early detection of conditions such as vascular and pulmonary diseases. Current methods for centerline tracking suffer from predicting topologically incorrect centerlines and complex model pipelines. To mitigate these issues we propose Trexplorer, a recurrent DETR based model that tracks topologically correct centerlines of tubular tree objects in 3D volumes using a simple model pipeline. We demonstrate the model's performance on a publicly available synthetic vessel centerline dataset and show that our model outperforms the state-of-the-art on centerline topology and graph-related metrics, and performs well on detection metrics. The code is available at https://github.com/RomStriker/Trexplorer.

tracking

tree topology

centerline

Author

Roman Naeem

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

David Hagerman Olzon

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Lennart Svensson

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Fredrik Kahl

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Lecture Notes in Computer Science

0302-9743 (ISSN) 16113349 (eISSN)

Vol. 15011 744-754
978-3-031-72119-9 (ISBN)

27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
Marrakesh, Morocco,

Subject Categories

Bioinformatics (Computational Biology)

Medical Image Processing

DOI

10.1007/978-3-031-72120-5_69

More information

Latest update

12/9/2024