Analysis and strategies to enchance intensity-based image registration
Roshni R. Bhagalia · 2008
ANALYSIS AND STRATEGIES TO ENHANCE INTENSITY-BASED IMAGE REGISTRATION by Roshni R. Bhagalia Co-chairs: Jeffrey A. Fessler and Boklye Kim The availability of numerous complementary imaging modalities allows us to obtain a detailed picture of the body and its functioning. To aid diagnostics and surgical planning, all available information can be presented by visually aligning images from different modalities using image registration. This dissertation investigates strategies to improve the performance of image registration algorithms that use intensity-based similarity metrics. Nonrigid warp estimation using intensity-based registration can be very time consuming. We develop a novel framework based on importance sampling and stochastic approximation techniques to accelerate nonrigid registration methods while preserving their accuracy. Registration results for simulated brain MRI data and human lung CT data demonstrate the efficacy of the proposed framework. Functional MRI (fMRI) is used to non-invasively detect brain-activation by acquiring a series of brain images, called a time-series, while the subject performs tasks designed to stimulate parts of the brain. Consequently, these studies are plagued by subject head motion. Mutual information (MI) based slice-to-volume (SV) registration algorithms used