Unified Deterministic/Statistical Deformable Models for Cardiac Image Analysis
نویسنده
چکیده
OF THE DISSERTATION Unified Deterministic/Statistical Deformable Models for Cardiac Image Analysis by Sharath Kumar Gopal Doctor of Philosophy in Computer Science University of California, Los Angeles, 2016 Professor Demetri Terzopoulos, Chair This thesis proposes to fully automate the shape and motion reconstruction of non-rigid objects from visual information using a unified deterministic/statistical deformable model. The model enhances the global control of a statistical deformable model with local control, based on assumptions of the material properties of the non-rigid object being modeled. A Histogram of Oriented Gradients (HoG) based object detector for a 3D volume is proposed to compute initial model estimates that are crucial for automation. This thesis also develops a unified variational method for 4D (3D+time) non-rigid shape reconstruction with anatomical and temporal smoothness constraints. The proposed unified model and method are combined in a fully automated Computer Vision and Machine Learning based framework for the clinically important application of segmenting the myocardium in cardiac cine Magnetic Resonance images.
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