Automatic and Semi-automatic Analysis of the Extension of Myocardial Infarction in an Experimental Murine Model
Rodent models of myocardial infarction (MI) have been extensively used in biomedical research towards the implementation of novel regenerative therapies. Permanent ligation of the left anterior descending (LAD) coronary artery is a commonly used method for inducing MI both in rat and mouse. Post-mortem evaluation of the heart, particularly the MI extension assessment performed on histological sections, is a critical parameter for this experimental setting. MI extension, which is defined as the percentage of the left ventricle affected by the coronary occlusion, has to be estimated by identifying the infarcted- and the normal-tissue in each section. However, because it is a manual procedure it is time-consuming, arduous and prone to bias. Herein, we introduce semi-automatic and automatic approaches to perform segmentation which is then used to obtain the infarct extension measurement. Experimental validation is performed comparing the proposed approaches with manual annotation and a total error not exceeding 8% is reported in all cases.
KeywordsInfarct extension evaluation image segmentation region growing otsu k-means meanshift watershed
Unable to display preview. Download preview PDF.
- 4.Wu, Q., Merchant, F., Castleman, K.: Microscope Image Processing, ch. 7. Elsevier, Amsterdam (1996)Google Scholar
- 5.Gonzalez, R., Woods, R., Eddins, S.: Digital Image Processing Using MATLAB, ch. 9. Pearson Education, London (2004)Google Scholar
- 9.Khadir, S., Ahamed, R.: Moving toward region-based image segmentation techniques: A study. Journal of Theoretical and Applied Information Technology 5(1), 1–7 (2009)Google Scholar
- 10.Ahmed, M., Mohamad, D.: Segmentation of brain mr images for tumor extraction by combining kmeans clustering and perona-malik anisotropic diffusion model. International Journal of Image Processing 2(1), 1–8 (2010)Google Scholar