Fully automated reconstruction of ungated ghost magnetic resonance angiograms

Purpose: To completely automate the reconstruction process during noncardiac‐gated unenhanced ghost magnetic resonance angiography (MRA). Materials and Methods: Ungated unenhanced ghost MRA of the calf was performed in 16 volunteers. K‐means and fuzzy c‐means (FCM) clustering algorithms using promin...

Full description

Saved in:

Bibliographic Details
Published in:	Journal of magnetic resonance imaging Vol. 31; no. 3; pp. 655 - 662
Main Authors:	Tsaftaris, Sotirios A., Offerman, Erik, Edelman, Robert R., Koktzoglou, Ioannis
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.03.2010
Subjects:	Adult Algorithms Cardiac-Gated Imaging Techniques cluster analysis Female ghost angiography Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods image reconstruction Leg - anatomy & histology Leg - blood supply Magnetic Resonance Angiography - methods Male Middle Aged Pattern Recognition, Automated - methods Reproducibility of Results Sensitivity and Specificity Young Adult
ISSN:	1053-1807, 1522-2586, 1522-2586
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Purpose: To completely automate the reconstruction process during noncardiac‐gated unenhanced ghost magnetic resonance angiography (MRA). Materials and Methods: Ungated unenhanced ghost MRA of the calf was performed in 16 volunteers. K‐means and fuzzy c‐means (FCM) clustering algorithms using prominent image features were applied to automatically create angiograms of the calf in volunteers undergoing ungated ghost MRA. Ghost angiograms reconstructed automatically were compared to those created manually on the basis of diagnostic image quality and apparent arterial‐to‐background contrast‐to‐noise ratio (CNR). Images were also ranked by an expert user in their order of preference using an ordinal scale. Results: Compared with the ghost angiograms created manually, ghost angiograms reconstructed automatically with the use of clustering analysis provided similar arterial‐to‐background CNR values. No differences in diagnostic quality or preference were identified between images reconstructed manually and automatically. Conclusion: We present fully automated image reconstruction algorithms for use with ungated and unenhanced ghost MRA. These automated algorithms, based on the use of k‐means or FCM clustering, can be used to eliminate manual postprocessing that is time‐consuming and subject to variability. J. Magn. Reson. Imaging 2010;31:655–662. © 2010 Wiley‐Liss, Inc.
Bibliography:	ark:/67375/WNG-PZN0KQ89-8 istex:F9533BF9DDD01F6E75C6D9F2C9C04FFD2FC5A395 The Grainger Foundation and The Auxiliary of NorthShore University HealthSystem ArticleID:JMRI22092 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1053-1807 1522-2586 1522-2586
DOI:	10.1002/jmri.22092