Carmel Hayes

Edgar Mueller

Jens Guehring

Marie-Pierre Jolly

Michaela Schmidt

Peter Kellman

Peter Speier

Randall Kroeker

Xiaoguang Lu

Xiaoming Bi

Zheng

English

PubMed

Guehring Jens

Hayes Carmel

Speier Peter

Schmidt Michaela

Kroeker Randall

Bi Xiaoming

Jolly Marie-Pierre

Lu Xiaoguang

Kellman Peter

Mueller Edgar

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Journal of Cardiovascular Magnetic Resonance

Automatic LV localization and view planning for cardiac MRI acquisition

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POSTER PRESENTATION Open Access
Automatic LV localization and view planning for
cardiac MRI acquisition
Peter Kellman1*, Xiaoguang Lu2, Marie-Pierre Jolly2, Xiaoming Bi3, Randall Kroeker4, Michaela Schmidt5,
Peter Speier5, Carmel Hayes5, Jens Guehring2, Edgar Mueller5
From 2011 SCMR/Euro CMR Joint Scientific Sessions
Nice, France. 3-6 February 2011
Background
Localization of the heart is typically performed using a
multi-step approach involving the acquisition of double-
oblique localizer images. Based on the localizers the
standard heart views are planned. This approach is
operator-dependent and time consuming.
Objective
To demonstrate feasibility of a fully automatic and fast
approach to heart localization and slice prescription
from a highly-accelerated, single breath-hold 3D acquisi-
tion through a machine learning method.
Methods
A 3D full-chest MR scan is obtained through parallel
imaging within a single breath-hold. A single volume is
acquired at mid-diastole using an ECG gated segmented
acquisition with T2-prepared SSFP readout with chemi-
cal shift fat suppression. Typical protocol parameters
are: 400x400x220 mm3 FOV prescribed as a coronal
1National Institutes of Health, Bethesda, MD, USA
Full list of author information is available at the end of the article
Figure 1 Workflow of automatic LV localization and view planning.
Kellman et al. Journal of Cardiovascular Magnetic Resonance 2011, 13(Suppl 1):P39
http://jcmr-online.com/content/13/S1/P39
© 2011 Kellman et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
slab (256x202x44 matrix; 1.6x2x5 mm3 resolution, inter-
polated to 2.5 mm slices). Images are acquired using a
1.5T Siemens Avanto/Espree with 32 channel coil and
parallel imaging with rate 6=3x2 (PE in LR direction x
PAR in AP direction) and ¾ partial Fourier in PAR
dimension. Breath-hold duration is typically less than
20s with all PE lines acquired in a single shot per
heartbeat.
We train a series of detectors on a database with
manually delineated LV to estimate the LV pose and
boundaries using probabilistic boosting trees [1] and
marginal space learning [2]. The short axis stack is
planned based on the delineated LV. To prescribe the
VLA and HLA views, we choose a mid-ventricular short
axis slice, and apply a landmark detection algorithm [3]
to localize the RV insertion points, and the RV lateral
point (Figure 1). The VLA view is calculated to be paral-
lel to the line connecting the RV insertion points and to
cross the LV blood pool center. The HLA view is com-
puted to cross the LV blood pool center and the RV lat-
eral point.
Results
We collected 49 MR volumes and manually delineated
LV on 27 volumes. We apply our method and visually
inspect the results. For cases with full LV coverage, our
method delineates LV sufficiently accurate for planning
purposes (mean error: 2.10mm, standard deviation:
0.98mm). Failures are mostly due to partial LV coverage.
Conclusion
We successfully demonstrated feasibility of a fully auto-
matic and fast approach to heart localization and slice
prescription from a single breath-hold 3D scan in less
than 30 seconds. Further investigations to characterize
the performance and robustness of the method are
warranted.
Author details
1National Institutes of Health, Bethesda, MD, USA. 2Siemens Corporate
Research, Princeton, NJ, USA. 3Siemens Medical Solutions USA, Chicago, IL,
USA. 4Siemens Medical Solutions, Canada, Winnipeg, MB, Canada. 5Siemens
AG, Healthcare Sector, Erlangen, Germany.
Published: 2 February 2011
References
1. Tu: ICCV 2005.
2. Zheng: ICCV 2007.
3. Lu: MICCAI 2010.
doi:10.1186/1532-429X-13-S1-P39
Cite this article as: Kellman et al.: Automatic LV localization and view
planning for cardiac MRI acquisition. Journal of Cardiovascular Magnetic
Resonance 2011 13(Suppl 1):P39.
Figure 2 Examples of automatically localized LV
Kellman et al. Journal of Cardiovascular Magnetic Resonance 2011, 13(Suppl 1):P39
http://jcmr-online.com/content/13/S1/P39
Page 2 of 2


doi:10.1186/1532-429X-13-S1-P39 Cite this article as: Kellman et al.: Automatic LV localization and view planning for cardiac MRI acquisition.

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Automatic LV localization and view planning for cardiac MRI acquisition

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