In pre-clinical research, whole-body small-animal imaging is widely used for in vivo visualization of functional and anatomical information to study cancer, neurological and cardiovascular diseases... Show moreIn pre-clinical research, whole-body small-animal imaging is widely used for in vivo visualization of functional and anatomical information to study cancer, neurological and cardiovascular diseases and help with a faster development of new drugs. Functional information is provided by imaging modalities such as PET, SPECT and specialized MRI. Structural imaging modalities like CT, MRI and ultrasound provide detailed depictions of anatomy. Optical imaging modalities, such as BLI and near-infrared-fluorescence offer a high sensitivity in visualizing molecular processes in vivo. Combining these modalities enables to follow the subject(s) and molecular processes in time, in living animals. With these advances in image acquisition, the problem has shifted from data acquisition to data processing: organization, analysis and interpretation of this heterogeneous whole-body imaging data has become a demanding task. Here, our data processing approach is based on an articulated whole-body atlas as a common reference to normalize the geometric heterogeneity caused by postural and anatomical differences between individuals and geometric differences between imaging modalities. Mapping to this atlas has the advantage that all the different imaging modalities can be registered to a common anatomical reference; postural variations can be corrected, and the different animals can be scaled properly while allowing for proper management of this high-throughput data. Show less
Coronary artery disease(CAD) is one of the leading causes of mortality and morbidity worldwide. Clinically, it refers to atherosclerotic changes in the coronary arteries and is usually assessed... Show moreCoronary artery disease(CAD) is one of the leading causes of mortality and morbidity worldwide. Clinically, it refers to atherosclerotic changes in the coronary arteries and is usually assessed with a stress electrocardiogram and conventional coronary angiography(CCA). CCA, however, is an invasive technique and carries a small risk of complications. Non-invasive techniques such as coronary angiography with CT(CTCA), and myocardial perfusion imaging (MPI) with SPECT and MR are therefore used as gatekeeper tests before CCA. These techniques provide valuable information on both the coronary stenoses and their hemodynamic impact on the myocardial function. However, each of these techniques presents only one aspect of CAD. To achieve a higher level of accuracy and precision in CAD assessment, integration of information from different cardiac imaging modalities is essential. The goal of this thesis was therefore to develop techniques to realize this multimodal diagnostic image integration to enhance CAD diagnosis. To this end, we developed novel algorithms for near automated analysis of magnetic resonance based myocardial perfusion images. In addition, we developed and evaluated a new integration framework that allows comprehensive visualization of physiologic information from myocardial perfusion imaging -either with MR or SPECT and anatomical information from CTCA Show less
