This　paper　proposes　a　circular　shape　constraint　and　a　novel　two-layer　level　set　method　for　the　segmentation　of　the　left　ventricle　(LV)　from　short-axis　magnetic　resonance　images　without　training　any　shape　models.　Since　the　shape　of　LV　throughout　the　apex-base　axis　is　close　to　a　ring　shape,　we　propose　a　circle　fitting　term　in　the　level　set　framework　to　detect　the　endocardium.　The　circle　fitting　term　imposes　a　penalty　on　the　evolving　contour　from　its　fitting　circle,　and　thereby　handles　quite　well　with　issues　in　LV　segmentation,　especially　the　presence　of　outflow　track　in　basal　slices　and　the　intensity　overlap　between　TPM　and　the　myocardium.　To　extract　the　whole　myocardium,　the　circle　fitting　term　is　incorporated　into　two-layer　level　set　method.　The　endocardium　and　epicardium　are　respectively　represented　by　two　specified　level　contours　of　the　level　set　function,　which　are　evolved　by　an　edge-based　and　a　region-based　active　contour　model.　The　proposed　method　has　been　quantitatively　validated　on　the　public　data　set　from　MICCAI　2009　challenge　on　the　LV　segmentation.　Experimental　results　and　comparisons　with　state-of-the-art　demonstrate　the　accuracy　and　robustness　of　our　method.　(C)　2017　Elsevier　Inc.　All　rights　reserved.