Heart chambers and whole heart segmentation techniques: review

Abstract

Noninvasive cardiac imaging is an invaluable tool for the diagnosis and treatment of cardiovascular disease (CVD). Magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), and ultrasound (US) have been used extensively for physiologic understanding and diagnostic purposes in cardiology. These imaging technologies have greatly increased our understanding of normal and diseased anatomy. Cardiac image segmentation plays a crucial role and allows for a wide range of applications, including quantification of volume, computer-aided diagnosis, localization of pathology, and image-guided interventions. However, manual delineation is tedious, time-consuming, and is limited by inter- and intraobserver variability. In addition, many segmentation algorithms are sensitive to the initialization and therefore the results are not always reproducible, which is also limited by interalgorithm variability. Furthermore, the amount and quality of imaging data that needs to be routinely acquired in one or more subjects has increased significantly. Therefore, it is crucial to develop automated, precise, and reproducible segmentation methods. Figure 1 illustrates an example of segmentation of heart on CT scan.