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1124 Automated soft segmentation of the left ventricle using myocardial effusion threshold reduction and intravoxel computation (METRIC)


An automated partial voxel left ventricular segmentation algorithm is presented. The algorithm, termed LV-METRIC (Left Ventricular Myocardial Effusion Threshold Reduction with Intravoxel Computation), measures the blood volume of the LV from cardiac cine MRI images, for all phases and slices. Papillary muscle and trabecular muscles are accounted for through partial voxel interpolation. Minimal interaction is required in some basal slices for which the valve plane must be defined.


1) A Hough transform is performed on the subtraction of images from phases 1 and 10 of a mid-ventricular slice [14]. 2) Edge-based region-growth is performed to discover the mean and standard deviation (μ b /σ b ) of full-blood voxels. 3) A planar surface is fit to full-blood voxels to compensate for coil sensitivity variations. 4) Successive lower-bound threshold based region-growth processes are run for an iteratively decreasing threshold to estimate the myocardial mean. Eventually, region-growth breaks through the myocardium, "effusing" into surrounding structures. This effusion threshold is strongly related to the mean (μ m ). 5) The total blood volume is determined by the summation of the histogram multiplied by a linear weighting function between (μb- b )) and (μ m + b ). 6) An energy function of distance from the center of mass and intensity difference is used to find the next seed point.

Materials and methods

The study included 38 randomly selected patients (15 male, mean age 52.4 years ± 15.1 standard deviation), including 20 referred for clinical cardiac MRI and 18 with normal systolic function (based on a-priori MT). The most common clinical indications for referral were assessment of presence or pattern of myocardial scar. This study was approved by our IRB. Scans were performed using a GE Signa 1.5 T scanner, imaging parameters TR 3.3–4.5 ms, TE 1.1–2.0 ms, flip angle 55–60, matrix size 192 × 192 – 256 × 256, image dimensions 256 × 256, receiver bandwidth 125 kHz, FOV 290–400 × 240–360, slice thickness and slice gap 6–8 mm & 2–4 mm, respectively (total 10 mm). The LV in each patient was imaged in 6–10 slices, 20–28 cardiac phases. Two LV-METRIC volume measurements were compared to expert manual tracing (MT) measurements that excluded papillary muscles from the blood volume according to established criteria [5, 6]. In the first measurement, LV-METRIC linearly interpolated the blood content of voxels. In the second, all partial-blood voxels are considered full-blood. Student's t-test was used to determine statistical significance.


Figures 1 and 2 show example LV-METRIC and manual segmentations. Blue to green denotes blood content from least to most. The absolute and relative differences between MT and LV-METRIC linearly interpolating partial-blood voxels are shown in Table 1. All differences were statistically significant. The differences considering all partial-blood voxels as full-blood voxels are shown in Table 2. No significant differences were observed.


Figure 1


Figure 2

Table 1 MT minus LV-METRIC with Linear Partial Voxel Interpolation. (x = MT)
Table 2 MT minus LV-METRIC with all partial-blood voxels counted as full-blood voxels. (x = MT)


While LV-METRIC volumes were smaller than manual tracing (MT) volumes, the LV-METRIC measurements that counted partial-blood voxels as full-blood voxels were similar to MT. Therefore, the difference between MT and LV-METRIC was likely due to partial voxel effects. In current breath hold 2D acquisition of cine SSFP images, the voxel size is limited to 1.4 × 1.4 × 10 mm3. Consequentially, voxels with mixed myocardium and blood are invariably present, which leads to volume overestimation. Further validation using phantoms and high resolution scans as comparison standards must be performed to conclusively show the accuracy of partial voxel measurements.


  1. 1.

    Geest van der RJ, et al.: J Cardiovasc Magn Reson. 2004, 6 (3): 609-617. 10.1081/JCMR-120038082.

    Article  PubMed  Google Scholar 

  2. 2.

    Pednekar A, et al.: IEEE Trans Biomed Eng. 2006, 53 (7): 1425-1428. 10.1109/TBME.2006.873684.

    Article  PubMed  Google Scholar 

  3. 3.

    Geest van der RJ, et al.: Journal of Computer Assisted Tomography. 1997, 21 (5): 756-765. 10.1097/00004728-199709000-00019.

    Article  PubMed  Google Scholar 

  4. 4.

    Illingworth J, et al.: Comput Vision Graph. 1988, 44 (1): 87-116. 10.1016/S0734-189X(88)80033-1.

    Article  Google Scholar 

  5. 5.

    Papavassiliu T, et al.: Radiology. 2005, 236 (1): 57-64. 10.1148/radiol.2353040601.

    Article  PubMed  Google Scholar 

  6. 6.

    Hudsmith LE, et al.: J Cardiovasc Magn Reson. 2005, 7 (5): 775-782. 10.1080/10976640500295516.

    Article  PubMed  Google Scholar 

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Correspondence to Noel Codella.

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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Codella, N., Weinsaft, J.W., Cham, M.D. et al. 1124 Automated soft segmentation of the left ventricle using myocardial effusion threshold reduction and intravoxel computation (METRIC). J Cardiovasc Magn Reson 10, A249 (2008).

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  • Coil Sensitivity
  • Manual Trace
  • Linear Weighting Function
  • Common Clinical Indication
  • Trabecular Muscle