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.
This paper presents a preliminary evaluation work on a pre-designed 3-D ultrasound imaging system. The system mainly consists of four parts, a 7.5MHz, 24×24 2-D array transducer, the transmit/receive circuit, power supply, data acquisition and real-time imaging module. The row-column addressing scheme is adopted for the transducer fabrication, which greatly reduces the number of active channels . The element area of the transducer is 4.6mm by 4.6mm. Four kinds of tests were carried out to evaluate the imaging performance, including the penetration depth range, axial and lateral resolution, positioning accuracy and 3-D imaging frame rate. Several strong reflection metal objects , fixed in a water tank, were selected for the purpose of imaging due to a low signal-to-noise ratio of the transducer. The distance between the transducer and the tested objects , the thickness of aluminum, and the seam width of the aluminum sheet were measured by a calibrated micrometer to evaluate the penetration depth, the axial and lateral resolution, respectively. The experiment al results showed that the imaging penetration depth range was from 1.0cm to 6.2cm, the axial and lateral resolution were 0.32mm and 1.37mm respectively, the imaging speed was up to 27 frames per second and the positioning accuracy was 9.2%.
This paper presents a work of real-time 3-D image reconstruction for a 7.5-MHz, 24×24 row-column addressing array transducer. The transducer works with a predesigned transmit/receive module. After the raw data are captured by the NI PXIe data acquisition (DAQ) module, the following processing procedures are performed: delay and sum (DAS), base-line calibration, envelope detection, logarithm compression, down-sampling, gray scale mapping and 3-D display. These procedures are optimized for obtaining real-time 3-D images. Fixed-point focusing scheme is applied in delay and sum (DAS) to obtain line data from channel data. Zero-phase high-pass filter is used to calibrate the base-line shift of echo. The classical Hilbert transformation is adopted to detect the envelopes of echo. Logarithm compression is implemented to enlarge the weak signals and narrow the gap from the strong ones. Down-sampling reduces the amount of data to improve the processing speed. Linear gray scale mapping is introduced that the weakest signal is mapped to 0 and the strongest signal 255. The real-time 3-D images are displayed with multi-planar mode, which shows three orthogonal sections (vertical section, coronal section, transverse section). A trigger signal is sent from the transmit/receive module to the DAQ module at the start of each volume data generation to ensure synchronization between these two modules. All procedures, include data acquisition (DAQ), signal processing and image display, are programmed on the platform of LabVIEW. 675MB raw echo data are acquired in one minute to generate 24×24×48, 27fps 3-D images. The experiment on the strong reflection object (aluminum slice) shows the feasibility of the whole process from raw data to real-time 3-D images.