Abstract
This paper investigates automatic construction of a three-dimensional heart model from a set of medical images, represents it in a deformable shape, and uses it to perform volumetric measurements. This not only significantly improves its reliability and accuracy but also makes it possible to derive valuable novel information, like various assessment and dynamic volumetric measurements. The method is based on a flexible model trained from hundreds of patient image sets by a genetic algorithm, which takes advantage of complete segmentation of the heart shape to form a geometrical heart model. For an image set of a new patient, an interpretation scheme is used to obtain its shape and evaluate some important parameters. Apart from automatic evaluation of traditional heart functions, some new information of cardiovascular diseases may be recognized from the volumetric analysis.
Highlights
The research to diagnose and prevent cardiovascular diseases becomes more important than ever
This paper presented a model-based approach for volumetric analysis of human hearts, especially for the ventricles, which is very important for diagnosis and treatment of cardiovascular diseases
Based on the flexible model trained from hundreds of patient images, a new patient will be actively analyzed to obtain its individual shape
Summary
The research to diagnose and prevent cardiovascular diseases becomes more important than ever. Thanks to the newly developed technologies in medical imaging and computing, automatic evaluation of patient hearts becomes possible. This is very useful for diagnosis and treatment. Yamamuro et al carried out a project on two-dimensional (2D) image processing [7] They evaluate accuracy of cardiac functional analysis with multidetector-row computed tomography (CT) and segmental reconstruction algorithm over a range of heart rates. The algorithm operates in the three-dimensional (3D) space and uses gated short-axis image volumes It segments the ventricle, estimates and displays endocardial and epicardial surfaces for all gating intervals in the cardiac cycle, calculates the relative left ventricular cavity volumes, and derives the global ejection fraction from the end-diastolic and end-systolic volume.
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