Cooperation between Local and Global Approaches to Register Brain Images

In this paper, we investigate the introduction of cortical constraints for non rigid inter-subject brain registration. We extract sulcal patterns with the active ribbon method, presented in [10]. An energy based registration method [7] makes it possible to incorporate the matching of cortical sulci, and express in a unified framework the local sparse similarity and the global "iconic" similarity. We show the objective benefits of cortical constraints on a database of 18 subjects, with global and local measures of the quality of the registration

DEVELOPMENT AND APPLICATIONS OF FEATURE-GUIDED CARDIAC MOTION ESTIMATION METHODS FOR 4D CARDIAC PET

The aim of this dissertation research is to develop, implement and evaluate methods to extract useful information about cardiac motion and myocardial contractility from 4D cardiac PET images with much improved image quality. First, to reduce the influence of respiratory motion and improve the quality of cardiac PET images used in motion estimation, data-driven respiratory gating methods are proposed to allow accurate extraction of respiratory motion signal from the list-mode data. Time-of-flight PET information is incorporated into respiratory signal extraction, and background correction method is developed to improve the quality and accuracy of the extracted respiratory signal. The methods were applied and evaluated using clinical list-mode cardiac PET data. With improved image quality, anatomical feature such as papillary muscles and the interventricular sulcus become increasingly detectable in gated cardiac PET images. For more accurate cardiac motion estimation, these anatomical features in human heart were extracted and used in combination with a priori knowledge of cardiac function to guide the cardiac motion estimation process. Initial estimates of the cardiac motion vector field were obtained based on the motion of the features for the traditional optical-flow algorithm. For further improvement, motion of the anatomical feature was used as additional constraint in the motion estimation algorithm to reduce the effect of the classical aperture problem. Different from previous cardiac motion extraction and estimation studies that only provide qualitative evaluation of the motion estimation results due to unavailability of ground truth for clinical cardiac datasets, this study employed simulation data from a realistic digital phantom with known cardiac motion for both qualitative and quantitative evaluation. Motion estimation results from simulation data indicate the feature-based cardiac motion estimation method is able to improve the accuracy of the cardiac motion field estimates, especially for motion components parallel to edges and therefore difficult to estimate using the conventional optical-flow based method. The proposed research will allow PET imaging to provide unprecedented cardiac motion information in addition to its functional information thus improving diagnosis of cardiac diseases including perfusion and motion abnormalities, and patient care with reduced cost. Also, more accurate estimation of cardiac motion will help to further improve the quality of 4D cardiac PET imaging with cardiac motion compensation