Zur Hauptnavigation wechseln Zur Suche wechseln Zum Hauptinhalt wechseln

The 2014 liver ultrasound tracking benchmark

V. De Luca*, T. Benz, S. Kondo, L. König, D. Lübke, S. Rothlübbers, O. Somphone, S. Allaire, M. A. Lediju Bell, D. Y.F. Chung, A. Cifor, C. Grozea, M. Günther, J. Jenne, T. Kipshagen, M. Kowarschik, N. Navab, J. Rühaak, J. Schwaab, C. Tanner

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

The Challenge on Liver Ultrasound Tracking (CLUST) was held in conjunction with the MICCAI 2014 conference to enable direct comparison of tracking methods for this application. This paper reports the outcome of this challenge, including setup, methods, results and experiences. The database included 54 2D and 3D sequences of the liver of healthy volunteers and tumor patients under free breathing. Participants had to provide the tracking results of 90% of the data (test set) for pre-defined point-landmarks (healthy volunteers) or for tumor segmentations (patient data). In this paper we compare the best six methods which participated in the challenge. Quantitative evaluation was performed by the organizers with respect to manual annotations. Results of all methods showed a mean tracking error ranging between 1.4 mm and 2.1 mm for 2D points, and between 2.6 mm and 4.6 mm for 3D points. Fusing all automatic results by considering the median tracking results, improved the mean error to 1.2 mm (2D) and 2.5 mm (3D). For all methods, the performance is still not comparable to human inter-rater variability, with a mean tracking error of 0.5-0.6 mm (2D) and 1.2-1.8 mm (3D). The segmentation task was fulfilled only by one participant, resulting in a Dice coefficient ranging from 76.7% to 92.3%. The CLUST database continues to be available and the online leader-board will be updated as an ongoing challenge.

OriginalspracheEnglisch
Aufsatznummer5571
ZeitschriftPhysics in Medicine and Biology
Jahrgang60
Ausgabenummer14
Seiten (von - bis)5571-5599
Seitenumfang29
ISSN0031-9155
DOIs
PublikationsstatusVeröffentlicht - 07.07.2015

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen
  2. SDG 9 – Industrie, Innovation und Infrastruktur
    SDG 9 – Industrie, Innovation und Infrastruktur

Fingerprint

Untersuchen Sie die Forschungsthemen von „The 2014 liver ultrasound tracking benchmark“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren