Uzunbaş Mustafa Gökhan, Zhang Shaoting, Pohl Kilian M, Metaxas Dimitris, Axel Leon
CBIM, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Proc IEEE Int Symp Biomed Imaging. 2012 May;2012:254-257. doi: 10.1109/ISBI.2012.6235532. Epub 2012 Jul 12.
Deformable models and graph cuts are two standard image segmentation techniques. Combining some of their benefits, we introduce a new segmentation system for (semi-) automatic delineation of epicardium and endocardium of Left Ventricle of the heart in Magnetic Resonance Images (MRI). Specifically, a temporal information among consecutive phases is exploited via a coupling between deformable models and graph cuts which provides automated accurate cues for graph cuts and also good initialization scheme for deformable model that ultimately leads to more accurate and smooth segmentation results with lower interaction costs than using only graph cut segmentation. In addition, we define deformable model as a region defined by two nested contours and segment epicardium and endocardium in an unified way by optimizing single energy functional. This approach provides inherent coherency among the two contours thus leads to more accurate results than deforming separate contours for each target. We show promising results on the challenging problems of left ventricle segmentation.
可变形模型和图割是两种标准的图像分割技术。结合它们的一些优点，我们引入了一种新的分割系统，用于在磁共振图像（MRI）中（半）自动描绘心脏左心室的心肌外膜和心内膜。具体而言，通过可变形模型和图割之间的耦合来利用连续相位之间的时间信息，这为图割提供了自动准确的线索，也为可变形模型提供了良好的初始化方案，最终导致比仅使用图割分割具有更低交互成本的更准确和平滑的分割结果。此外，我们将可变形模型定义为由两个嵌套轮廓定义的区域，并通过优化单个能量泛函以统一的方式分割心肌外膜和心内膜。这种方法在两个轮廓之间提供了内在的一致性，因此比为每个目标变形单独的轮廓能得到更准确的结果。我们在具有挑战性的左心室分割问题上展示了有前景的结果。
