Title: RF-based motion estimation using non-rigid image registration techniques: in-silico and in-vivo feasibility
Authors: Heyde, Brecht
Alessandrini, Martino
Tong, Ling
D'hooge, Jan
Issue Date: Sep-2014
Host Document: IEEE International Ultrasonics Symposium pages:2280-2283
Conference: IEEE International Ultrasonics Symposium location:Chicago date:3-6 September
Abstract: US deformation techniques can roughly be divided
in block matching (BM) and non-rigid image registration (NRIR).
Motion can be extracted from the radio-frequency (RF) signals,
from their envelope, or from the B-mode data. RF-based BM is
known to outperform B-mode tracking in a small displacement
setting, whereas NRIR has only been applied to B-mode data.
The aim of this study was to test the feasibility of RF-based
NRIR in-silico and in-vivo. First, synthetic 2D images of a
phantom with a soft inclusion undergoing an axial compression
(0.25%) were simulated. Its performance was assessed by varying
the inclusion thickness (range: 2–20 mm in 2 mm steps) and
stiffness (resulting strain range: 0.50%–1.50% in 0.25% steps).
Both RF and envelope tracking were better at identifying smaller
and more subtle inclusions compared to B-mode tracking (down
to 8 mm and 6 mm resp.). Furthermore, when tracking the RF
instead of their envelope, inclusion borders were more sharply
defined (border size 2.57 mm vs 4.88 mm, p<0.001) and strain
errors in the inclusion were lower (0.08% vs 0.10%; p<0.05).
Next, NRIR was used to track the septum of a healthy volunteer
from high frame rate US recordings (436 Hz), and compared
against a recent RF-based BM method. In-vivo trackingrevealed
that RF-based BM and RF-based NRIR performed similarly,
both producing physiological axial velocity and strain curves.
The lateral components could only be estimated using NRIR.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Cardiovascular Imaging and Dynamics

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