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An Image-Based Comprehensive Approach for Automatic Segmentation of Left Ventricle from Cardiac Short Axis Cine MR Images.

Segmentation of the left ventricle is important in the assessment of cardiac functional parameters. Manual segmentation of cardiac cine MR images for acquiring these parameters is time-consuming. Accuracy and automation are the two important criteria in improving cardiac image segmentation methods....

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Published in:Journal of Digital Imaging Vol. 24; no. 4; pp. 598 - 609
Main Authors: Huang, Su, Liu, Jimin, Lee, Looi, Venkatesh, Sudhakar, Teo, Lynette, Au, Christopher, Nowinski, Wieslaw
Format: diagnostic images research tables/charts Journal Article
Published: Springer Nature Aug2011
Online Access:View this record in EBSCOhost
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      dt: Aug2011
      vid: 24
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10278-010-9315-4
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        atl: An Image-Based Comprehensive Approach for Automatic Segmentation of Left Ventricle from Cardiac Short Axis Cine MR Images.
      aug:
        au:
          Huang, Su
          Liu, Jimin
          Lee, Looi
          Venkatesh, Sudhakar
          Teo, Lynette
          Au, Christopher
          Nowinski, Wieslaw
        affil: Biomedical Imaging Lab, Singapore Bio-imaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore Singapore
      sug:
        subj:
          Heart Ventricle, Left Radiography
          Magnetic Resonance Imaging Methods
          Image Processing, Computer Assisted Methods
          Radiographic Image Interpretation, Computer-Assisted Methods
          Human
          Funding Source
          Diagnosis, Cardiovascular Methods
          Random Sample
          Algorithms
          Automation
      ab: Segmentation of the left ventricle is important in the assessment of cardiac functional parameters. Manual segmentation of cardiac cine MR images for acquiring these parameters is time-consuming. Accuracy and automation are the two important criteria in improving cardiac image segmentation methods. In this paper, we present a comprehensive approach to segment the left ventricle from short axis cine cardiac MR images automatically. Our method incorporates a number of image processing and analysis techniques including thresholding, edge detection, mathematical morphology, and image filtering to build an efficient process flow. This process flow makes use of various features in cardiac MR images to achieve high accurate segmentation results. Our method was tested on 45 clinical short axis cine cardiac images and the results are compared with manual delineated ground truth (average perpendicular distance of contours near 2 mm and mean myocardium mass overlapping over 90%). This approach provides cardiac radiologists a practical method for an accurate segmentation of the left ventricle.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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