A Registration-Based Propagation Framework for Automatic Whole Heart Segmentation of Cardiac MRI

作者：Zhuang Xiahai^*; Rhode Kawal S; Razavi Reza S; Hawkes David J; Ourselin Sebastien

来源：IEEE Transactions on Medical Imaging, 2010, 29(9): 1612-1625.

DOI：10.1109/TMI.2010.2047112

• Atlas
• cardiac magnetic resonance imaging (MRI)
• dynamic resampling and distance weighting interpolation (DRAW)
• free-form deformations
• image registration
• inverse transformation
• locally affine registration
• locally affine registration method (LARM)
• whole heart segmentation

Magnetic resonance (MR) imaging has become a routine modality for the determination of patient cardiac morphology. The extraction of this information can be important for the development of new clinical applications as well as the planning and guidance of cardiac interventional procedures. To avoid inter- and intra-observer variability of manual delineation, it is highly desirable to develop an automatic technique for whole heart segmentation of cardiac magnetic resonance images. However, automating this process is complicated by the limited quality of acquired images and large shape variation of the heart between subjects. In this paper, we propose a fully automatic whole heart segmentation framework based on two new image registration algorithms: the locally affine registration method (LARM) and the free-form deformations with adaptive control point status (ACPS FFDs). LARM provides the correspondence of anatomical substructures such as the four chambers and great vessels of the heart, while the registration using ACPS FFDs refines the local details using a constrained optimization scheme. We validated our proposed segmentation framework on 37 cardiac MR volumes on the end-diastolic phase, displaying a wide diversity of morphology and pathology, and achieved a mean accuracy of 2.14 +/- 0.63 mm (rms surface distance) and a maximal error of 4.31 mm.

• 出版日期2010-9