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

Saved in:
Bibliographic Details
Title: Novel Automated Motion Compensation Technique for Producing Cumulative Maximum Intensity Subharmonic Images
Authors: Dave, Jaydev K.1,2, Forsberg, Flemming1 flemming.forsberg@jefferson.edu
Source: Ultrasound in Medicine & Biology. Sep2009, Vol. 35 Issue 9, p1555-1563. 9p.
Subjects: Image stabilization, Breast imaging, Algorithms, Contrast-enhanced ultrasound, Breast disease diagnosis, Image processing, Breast cancer, Breast tumors, Comparative studies, Diagnostic imaging, Research methodology, Medical cooperation, Computers in medicine, Research, Research evaluation, Ultrasonic imaging, Pilot projects, Evaluation research, Body movement, Ductal carcinoma, Medical artifacts, Connective tissue tumors
Abstract: Abstract: 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: flemming.forsberg@jefferson.edu) [Copyright &y& Elsevier]
Copyright of Ultrasound in Medicine & Biology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 43874504
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Novel Automated Motion Compensation Technique for Producing Cumulative Maximum Intensity Subharmonic Images
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Dave%2C+Jaydev+K%2E%22">Dave, Jaydev K.</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Forsberg%2C+Flemming%22">Forsberg, Flemming</searchLink><relatesTo>1</relatesTo><i> flemming.forsberg@jefferson.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Ultrasound+in+Medicine+%26+Biology%22">Ultrasound in Medicine & Biology</searchLink>. Sep2009, Vol. 35 Issue 9, p1555-1563. 9p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Image+stabilization%22">Image stabilization</searchLink><br /><searchLink fieldCode="DE" term="%22Breast+imaging%22">Breast imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Contrast-enhanced+ultrasound%22">Contrast-enhanced ultrasound</searchLink><br /><searchLink fieldCode="DE" term="%22Breast+disease+diagnosis%22">Breast disease diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Breast+cancer%22">Breast cancer</searchLink><br /><searchLink fieldCode="DE" term="%22Breast+tumors%22">Breast tumors</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+studies%22">Comparative studies</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnostic+imaging%22">Diagnostic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+cooperation%22">Medical cooperation</searchLink><br /><searchLink fieldCode="DE" term="%22Computers+in+medicine%22">Computers in medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Research%22">Research</searchLink><br /><searchLink fieldCode="DE" term="%22Research+evaluation%22">Research evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Ultrasonic+imaging%22">Ultrasonic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Pilot+projects%22">Pilot projects</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+research%22">Evaluation research</searchLink><br /><searchLink fieldCode="DE" term="%22Body+movement%22">Body movement</searchLink><br /><searchLink fieldCode="DE" term="%22Ductal+carcinoma%22">Ductal carcinoma</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+artifacts%22">Medical artifacts</searchLink><br /><searchLink fieldCode="DE" term="%22Connective+tissue+tumors%22">Connective tissue tumors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Abstract: 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: flemming.forsberg@jefferson.edu) [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Ultrasound in Medicine & Biology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=43874504
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ultrasmedbio.2009.04.016
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 1555
    Subjects:
      – SubjectFull: Image stabilization
        Type: general
      – SubjectFull: Breast imaging
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Contrast-enhanced ultrasound
        Type: general
      – SubjectFull: Breast disease diagnosis
        Type: general
      – SubjectFull: Image processing
        Type: general
      – SubjectFull: Breast cancer
        Type: general
      – SubjectFull: Breast tumors
        Type: general
      – SubjectFull: Comparative studies
        Type: general
      – SubjectFull: Diagnostic imaging
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Medical cooperation
        Type: general
      – SubjectFull: Computers in medicine
        Type: general
      – SubjectFull: Research
        Type: general
      – SubjectFull: Research evaluation
        Type: general
      – SubjectFull: Ultrasonic imaging
        Type: general
      – SubjectFull: Pilot projects
        Type: general
      – SubjectFull: Evaluation research
        Type: general
      – SubjectFull: Body movement
        Type: general
      – SubjectFull: Ductal carcinoma
        Type: general
      – SubjectFull: Medical artifacts
        Type: general
      – SubjectFull: Connective tissue tumors
        Type: general
    Titles:
      – TitleFull: Novel Automated Motion Compensation Technique for Producing Cumulative Maximum Intensity Subharmonic Images
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Dave, Jaydev K.
      – PersonEntity:
          Name:
            NameFull: Forsberg, Flemming
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Text: Sep2009
              Type: published
              Y: 2009
          Identifiers:
            – Type: issn-print
              Value: 03015629
          Numbering:
            – Type: volume
              Value: 35
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Ultrasound in Medicine & Biology
              Type: main
ResultId 1