Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography

Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography by Jang Hwan Cho Chair: Jeffrey A. Fessler X-ray computed tomography (CT) is one of the most widely used imaging modalities for medical diagnosis. Recent advancements in CT scanner technology have led to increased use of CT in various applications. Unfortunately, these technological advances in CT imaging pose new challenges such as increased X-ray radiation dose and complexity of image reconstruction. Statistical image reconstruction methods use realistic models that incorporate the physics of the measurements and the statistical properties of the measurement noise, and they have potential to provide better image quality and dose reduction compared to the conventional filtered back-projection (FBP) method. However, statistical methods face several challenges that should be addressed before they can replace the FBP method universally. Such challenges include substantial computation time, anisotropic and nonuniform spatial resolution and noise properties, and other artifacts. In this thesis, we develop various methods to overcome these challenges of statistical image reconstruction methods. Rigorous regularization design methods in Fourier domain were proposed to achieve more isotropic and uniform spatial resolution or noise properties. The design framework is general so that users can control the spatial resolution and the noise characteristics of the estimator. Experimental results show the proposed method can achieve its goal with modest computation cost. In addition, a regularization design method based on the hypothetical geometry concept was introduced to improve resolution or noise uniformity. Proposed designs using the new concept effectively improved the spatial resolution or noise uniformity in the reconstructed image. The hypothetical geometry idea is general enough to be applied to other scan geometries. We investigated various methods to reduce image artifacts in reconstructed images caused by the short-scan geometry. Statistical weighting modification, based on how much each detector