Anatomical objects in medical images very often have dual contours or surfaces that are highly correlated. Manually segmenting both of them by following local image details is tedious and subjective. In this study, we proposed a two-layer region-based level set method with a soft distance constraint, which not only regularizes the level set evolution at two levels, but also imposes prior information on wall thickness in an effective manner. By updating the level set function and distance constraint functions alternatingly, the method simultaneously optimizes both contours while regularizing their distance. The method was applied to segment the inner and outer wall of both left atrium (LA) and left ventricle (LV) from MR images, using a rough initialization from inside the blood pool. Compared to manual annotation from experience observers, the proposed method achieved an average perpendicular distance (APD) of less than 1mm for the LA segmentation, and less than 1.5mm for the LV segmentation, at both inner and outer contours. The method can be used as a practical tool for fast and accurate dual wall annotations given proper initialization.
Catheter ablation is an important option to treat ventricular tachycardias (VT). Scar-related VT is among the most
difficult to treat, because myocardial scar, which is the underlying arrhythmogenic substrate, is patient-specific and
often highly complex. The scar image from preprocedural late gadolinium enhancement magnetic resonance
imaging (LGE- MRI) can provide high-resolution substrate information and, if integrated at the early stage of the
procedure, can largely facilitate the procedure with image guidance. In clinical practice, however, early MRI
integration is difficult because available integration tools rely on matching the MRI surface mesh and
electroanatomical mapping (EAM) points, which is only possible after extensive EAM has been performed.
In this paper, we propose to use a priori information on patient posture and a multi-sequence MRI integration
framework to achieve accurate MRI integration that can be accomplished at an early stage of the procedure. From
the MRI sequences, the left ventricular (LV) geometry, myocardial scar characteristics, and an anatomical landmark
indicating the origin of the left main coronary artery are obtained preprocedurally using image processing techniques.
Thereby the integration can be realized at the beginning of the procedure after acquiring a single mapping point. The
integration method has been evaluated postprocedurally in terms of LV shape match and actual scar match.
Compared to the iterative closest point (ICP) method that uses high-intensity mapping (225±49 points), our method
using one mapping point reached a mean point-to-surface distance of 5.09±1.09 mm (vs. 3.85±0.60 mm, p<0.05),
and scar correlation of -0.51±0.14 (vs. -0.50±0.14, p=NS).