Sammendrag
Ultrasound has been shown to be a powerful imaging
tool for the evaluation of musculoskeletal disease (e.g. rheumatoid
arthritis or carpal tunnel syndrome). Power Doppler imaging
in particular plays an important role in treatment monitoring.
However it is also known that ultrasound is operator dependent
and has low intra- and inter-observer repeatability. The aim of
this work was to reduce the uncertainty of the follow-up process
of a typical musculoskeletal exam by ensuring that the same
anatomy is visualized at baseline and follow-up.
A visualization tool, which receives a continuous stream of
ultrasound data, has been implemented in Qt. The streamed
images are compared on the fly against a pre-loaded baseline
image. To compensate for in plane translation and rotation differences,
2D rigid registration is performed. Normalized mutual
information was used as a similarity metric and is color coded
from red (0%) to green (100%) to show the amount of similarity
among the current images. Several display alternatives (e.g. semitransparent
overlay, color coded overlay) have been implemented
and tested. Optional anisotropic filtering can be applied to both
images before registration to reduce the impact of the speckle
noise on the final result.
Two healthy volunteers and a phantom have been used for
validation purposes. Both the reference and follow-up ultrasound
data have been acquired with a Vivid E9 scanner, with an ML6-15
probe (GE Vingmed Ultrasound). At the same time the position
of the probe with regards to a reference frame was tracked with
an accurate optical position sensor (Polaris, NDI). It was shown
that the highest similarity scores corresponded to the lowest
translation offsets and angle differences. The average offset and
angle errors for the patient data were: [0.68 ± 0.97, 0.47 ± 0.79,
-2.28 ± 1.38]mm, [2.92 ± 2.35, -0.17 ± 1.2, 1.24 ± 2.38]◦.
A novel method for real-time fusion of ultrasound images
aimed at musculoskeletal disease monitoring has been presented.
Being provided with instant feedback, the user is more confident
during the acquisition process.
tool for the evaluation of musculoskeletal disease (e.g. rheumatoid
arthritis or carpal tunnel syndrome). Power Doppler imaging
in particular plays an important role in treatment monitoring.
However it is also known that ultrasound is operator dependent
and has low intra- and inter-observer repeatability. The aim of
this work was to reduce the uncertainty of the follow-up process
of a typical musculoskeletal exam by ensuring that the same
anatomy is visualized at baseline and follow-up.
A visualization tool, which receives a continuous stream of
ultrasound data, has been implemented in Qt. The streamed
images are compared on the fly against a pre-loaded baseline
image. To compensate for in plane translation and rotation differences,
2D rigid registration is performed. Normalized mutual
information was used as a similarity metric and is color coded
from red (0%) to green (100%) to show the amount of similarity
among the current images. Several display alternatives (e.g. semitransparent
overlay, color coded overlay) have been implemented
and tested. Optional anisotropic filtering can be applied to both
images before registration to reduce the impact of the speckle
noise on the final result.
Two healthy volunteers and a phantom have been used for
validation purposes. Both the reference and follow-up ultrasound
data have been acquired with a Vivid E9 scanner, with an ML6-15
probe (GE Vingmed Ultrasound). At the same time the position
of the probe with regards to a reference frame was tracked with
an accurate optical position sensor (Polaris, NDI). It was shown
that the highest similarity scores corresponded to the lowest
translation offsets and angle differences. The average offset and
angle errors for the patient data were: [0.68 ± 0.97, 0.47 ± 0.79,
-2.28 ± 1.38]mm, [2.92 ± 2.35, -0.17 ± 1.2, 1.24 ± 2.38]◦.
A novel method for real-time fusion of ultrasound images
aimed at musculoskeletal disease monitoring has been presented.
Being provided with instant feedback, the user is more confident
during the acquisition process.