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Program to manually track myocardium landmarks in short axis cardiac MR images using Python and OpenCV

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MyocardicalStrainMeasurement

Program to manually track myocardium landmarks in short axis cardiac MR images using Python and OpenCV

Background and relevant literature

Heart is a very vital organ in the human body. It is responsible for continuous circulation of blood to all the organs of the body. Therefore, the heart primarily acts as a pump. The motion and dynamics of the different regions of the heart have a very strong impact on its pumping efficiency. In short, the dynamics of heart motion during systole and diastole is a major factor indicative of cardiac health. Therefore, in the recent years, Myocardial strain measurement has gained increasing traction from the cardiovascular research community.

  • Bilchick, K.C., Dimaano, V., Wu, K.C., Helm, R.H., Weiss, R.G., Lima, J.A., Berger, R.D., Tomaselli, G.F., Bluemke, D.A., Halperin, H.R. and Abraham, T., 2008. Cardiac magnetic resonance assessment of dyssynchrony and myocardial scar predicts function class improvement following cardiac resynchronization therapy. JACC: Cardiovascular Imaging, 1(5), pp.561-568.

  • Albert C Lardo, Theodore P Abraham, and David A Kass, “Magnetic resonance imaging assessment of ventricular dyssynchrony: current and emerging concepts,”Journal of the American College of Cardiology, vol. 46,no. 12, pp. 2223–2228, 2005

Aim and overview

The aim of the current project is to develop a simple program to enable manual extraction and tracking of individual myocardial segments from multi slice stack of 2D short-axis (SAX) cine MRI images. Long term aims of the project are -

  • to facilitate a ground truth generation for myocardial strain measurements, which would be later used for comparative assessment of sophisticated tracking algorithms
  • gaining insights into the accuracy of already existing products on CircleCVI and other commercial software packages.

User manual and process description

The entire myocardial tracking process is divided into multiple steps

  1. Loading the dataset: Dataset contains multiple slice cine data of 2D short axis MRI. Dim [rows, cols, phases, slices]
  2. Selecting the Region of Interest (ROI)
  3. Drawing segments for each slice
  4. Performing tracking of Myocardial landmark points for all slices and phases
  5. Saving the preliminary settings and tracking results into Excel workbook and saving the images for inspection and video generation

Tracking steps

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Program to manually track myocardium landmarks in short axis cardiac MR images using Python and OpenCV

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