Original Contribution| Volume 35, ISSUE 9, P1555-1563, September 2009

Novel Automated Motion Compensation Technique for Producing Cumulative Maximum Intensity Subharmonic Images

  • Jaydev K. Dave
    Department of Radiology, Thomas Jefferson University, Philadelphia, PA

    School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA
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  • Flemming Forsberg
    Address correspondence to: Flemming Forsberg, Ph.D., Department of Radiology, Division of Ultrasound, Suite 763J, Main Building, 132 South 10th Street, Philadelphia, PA 19107.
    Department of Radiology, Thomas Jefferson University, Philadelphia, PA
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      The aim of this study was to develop a novel automated motion compensation algorithm for producing cumulative maximum intensity (CMI) images from subharmonic imaging (SHI) of breast lesions. SHI is a nonlinear contrast-specific ultrasound imaging technique in which pulses are received at half the frequency of the transmitted pulses. A Logiq 9 scanner (GE Healthcare, Milwaukee, WI, USA) was modified to operate in grayscale SHI mode (transmitting/receiving at 4.4/2.2 MHz) and used to scan 14 women with 16 breast lesions. Manual CMI images were reconstructed by temporal maximum-intensity projection of pixels traced from the first frame to the last. In the new automated technique, the user selects a kernel in the first frame and the algorithm then uses the sum of absolute difference (SAD) technique to identify motion-induced displacements in the remaining frames. A reliability parameter was used to estimate the accuracy of the motion tracking based on the ratio of the minimum SAD to the average SAD. Two thresholds (the mean and 85% of the mean reliability parameter) were used to eliminate images plagued by excessive motion and/or noise. The automated algorithm was compared with the manual technique for computational time, correction of motion artifacts, removal of noisy frames and quality of the final image. The automated algorithm compensated for motion artifacts and noisy frames. The computational time was 2 min compared with 60–90 minutes for the manual method. The quality of the motion-compensated CMI-SHI images generated by the automated technique was comparable to the manual method and provided a snapshot of the microvasculature showing interconnections between vessels, which was less evident in the original data. In conclusion, an automated algorithm for producing CMI-SHI images has been developed. It eliminates the need for manual processing and yields reproducible images, thereby increasing the throughput and efficiency of reconstructing CMI-SHI images. The usefulness of this algorithm can be further extended to other imaging modalities. (E-mail: [email protected])

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