Trexplorer: Recurrent DETR for Topologically Correct Tree Centerline Tracking
Paper i 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

Författare

Roman Naeem

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

David Hagerman Olzon

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Fredrik Kahl

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

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,

Ämneskategorier

Bioinformatik (beräkningsbiologi)

Medicinsk bildbehandling

DOI

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

Mer information

Senast uppdaterat

2024-12-09