Literature DB >> 25485425

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

Fausto Milletari, Vasileios Belagiannis, Nassir Navab, Pascal Fallavollita.   

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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Year:  2014        PMID: 25485425     DOI: 10.1007/978-3-319-10470-6_71

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  5 in total

1.  Automatic 3D reconstruction of electrophysiology catheters from two-view monoplane C-arm image sequences.

Authors:  Christoph Baur; Fausto Milletari; Vasileios Belagiannis; Nassir Navab; Pascal Fallavollita
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-11-28       Impact factor: 2.924

2.  Online tracking of interventional devices for endovascular aortic repair.

Authors:  Daniele Volpi; Mhd H Sarhan; Reza Ghotbi; Nassir Navab; Diana Mateus; Stefanie Demirci
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-05-16       Impact factor: 2.924

3.  Scale-space for empty catheter segmentation in PCI fluoroscopic images.

Authors:  Ketan Bacchuwar; Jean Cousty; Régis Vaillant; Laurent Najman
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-05-22       Impact factor: 2.924

4.  Robust navigation support in lowest dose image setting.

Authors:  Mai Bui; Felix Bourier; Christoph Baur; Fausto Milletari; Nassir Navab; Stefanie Demirci
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-10-28       Impact factor: 2.924

5.  Catheter segmentation in X-ray fluoroscopy using synthetic data and transfer learning with light U-nets.

Authors:  Marta Gherardini; Evangelos Mazomenos; Arianna Menciassi; Danail Stoyanov
Journal:  Comput Methods Programs Biomed       Date:  2020-02-29       Impact factor: 5.428

  5 in total

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