Objective: Respiratory motion correction is necessary to quantitative analysis of liver contrast-enhance
ultrasound (CEUS) image sequences. However, traditionally manual selecting reference image would affect the
accuracy of the respiratory motion correction. Methods First, the original high-dimensional ultrasound gray-level
image data was mapped into a two-dimensional space by using Laplacian Eigenmaps (LE). Then, the cluster
analysis was adopted using K-means, and the optimal ultrasound reference image could be gotten for respiratory
motion correction. Finally, this proposed method was validated on 18 CEUS cases of VX2 tumor in rabbit liver,
and the effectiveness of this method was demonstrated. Results After correction, the time-intensity curves
extracted from the region of interest of CEUS image sequences became smoother. Before correction, the average of
total mean structural similarity (TMSSIM) and the average of mean correlation coefficient (MCC) from image
sequences were 0.45±0.11 and 0.67±0.16, respectively. After correction, the two parameters were increased
obviously(P<0.001), and were 0.59±0.11 and 0.81±0.11, respectively. The average of deviation valve (DV) from
image sequences before correction was 92.16±18.12. After correction, the average was reduced to one-third of the
original value. Conclusions: The proposed respiratory motion method could improve the accuracy of the
quantitative analysis of CEUS by using the reference image based on the traditionally manual selection. This
method is operated simply and has a potential in clinical application.
Scanning probe acoustic microscope (SPAM) can be used to acquire the morphology image as well as the non-destructive internal structures acoustic image. However, the observations of the morphology image as well as the internal structures acoustic image of liver cancer cells in SPAM are few. In this paper, we cultured 4 different types of liver cancer cells on the silicon wafer and coverslip to observe their morphology images as well as acoustic images in SPAM, and made a preliminary study of the 8 types of cells specimens (hereinafter referred to as the silicon specimens and coverslips specimens). The experimental measurement results showed that some cellular pseudopodium were observed in the morphology images of the coverslip specimens while no such cellular pseupodium were appeared in the morphology images of the silicon specimens, which concluded that the living liver cancer cells were less likely to grow on the silicon wafer. SPAM provides a rapid and sensitive visual method for studying the morphology and internal structures of the cancer cells. The proposed method can be also used to obtain the morphology and internal information in both solid and soft material wafers, such as silicon and cells, with the resolution of nanometer scale.
Acquiring nondestructive internal structures acoustic image as well as the morphology images using scanning probe acoustic microscope (SPAM) is a challenge and no known metrology tools to identify the ultrasonic internal resolution and detectable depth of SPAM in a nondestructive way. Monitoring these defects necessitates the identification of their technical parameters of SPAM. In this paper, the specific materials (test phantoms) were designed and processed so that the ultrasound internal resolution of SPAM in nondestructive imaging of the embedded or buried substructures as well as the morphology images were measured. Experimental results demonstrated the successful identification of embedded or buried defects under the test phantom with the resolution of 50nm for SPAM as well as the detectable depth of more than 100μm.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.