Startseite
English
Erweiterte Suche
Durchblättern nach ...
Publikationen im Überblick
Ansprechpartner
Hilfe
DOI
 |
|
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Fast groupwise 4D deformable image registration for irregular breathing motion estimation.
In: (International Workshop on Biomedical Image Registration). Berlin [u.a.]: Springer, 2018. 37-46 (Lect. Notes Comput. Sc. ; 10883 LNCS)
Tumor heterogeneity can be assessed quantitatively by analyzing dynamic contrast-enhanced imaging modalities potentially leading to improvement in the diagnosis and treatment of cancer, for example of the lung. However, the acquisition of standard lung sequences is often compromised by irregular breathing motion artefacts, resulting in unsystematic errors when estimating tissue perfusion parameters. In this work, we illustrate implicit deformable image registration that integrates the Demons algorithm using the local correlation coefficient as a similarity measure, and locally adaptive regularization that enables incorporation of both spatial sliding motions and irregular temporal motion patterns. We also propose a practical numerical approximation of the regularization model to improve both computational time and registration accuracy, which are important when analyzing long clinical sequences. Our quantitative analysis of 4D lung Computed Tomography and Computed Tomography Perfusion scans from clinical lung trial shows significant improvement over state-of-the-art pairwise registration approaches.
Altmetric
Weitere Metriken?
Zusatzinfos bearbeiten
[➜Einloggen]
Publikationstyp
Artikel: Konferenzbeitrag
ISSN (print) / ISBN
0302-9743
e-ISSN
1611-3349
Konferenztitel
International Workshop on Biomedical Image Registration
Zeitschrift
Lecture Notes in Computer Science
Quellenangaben
Band: 10883 LNCS,
Seiten: 37-46
Verlag
Springer
Verlagsort
Berlin [u.a.]
Nichtpatentliteratur
Publikationen
Institut(e)
Institute for Machine Learning in Biomed Imaging (IML)