Fully automatic catheter localization in C-arm images using ł1-sparse coding

Milletari F, Navab N, Fallavollita P, Belagiannis V (2014)


Publication Type: Conference contribution

Publication year: 2014

Book Volume: 17

Pages Range: 570-577

Abstract

We propose a method to perform automatic detection and tracking of electrophysiology (EP) catheters in C-arm fluoroscopy sequences. Our approach does not require any initialization, is completely automatic, and can concurrently track an arbitrary number of overlapping catheters. After a pre-processing step, we employ sparse coding to first detect candidate catheter tips, and subsequently detect and track the catheters. The proposed technique is validated on 2835 C-arm images, which include 39,690 manually selected ground-truth catheter electrodes. Results demonstrated sub-millimeter detection accuracy and real-time tracking performances.

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APA:

Milletari, F., Navab, N., Fallavollita, P., & Belagiannis, V. (2014). Fully automatic catheter localization in C-arm images using ł1-sparse coding. In Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 570-577).

MLA:

Milletari, Fausto, et al. "Fully automatic catheter localization in C-arm images using ł1-sparse coding." Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention 2014. 570-577.

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