Fast Fully-Automatic Cardiac Segmentation in MRI Using MRF Model Optimization, Substructures Tracking and B-Spline Smoothing

• Published in: Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges Vol. 10663; pp. 91 - 100
• Main Authors: Grinias, Elias, Tziritas, Georgios
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• ISBN: 9783319755403; 3319755404
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-75541-0_10

We present a fast fully automatic method for cardiac segmentation in ED and ES short axis MRI. At first we extract a region where the whole heart is situated, using a new, time-based approach. Then, the segmentation in LV, myocardium and right ventricle (RV) is obtained for a slice in a basal ED slice where both cavities are well distinguished. The extracted regions are tracked for the whole slice sequence backwards and forwards in ED. In all cases the segmentation is based on MRF optimization in four classes, two for the blood areas, and one for the myocardium and the background. Subsequently the segmentation in the ES images is based on the result of ED segmentation. As the epicardium is not well delineated, a smoothing process based on spline curves is used for obtaining the final result. We consider that, with an unsupervised method, we have obtained good results for LV and satisfactory for the RV and the myocardium on the ACDC 2017 datasets.