Towards Ontology-Based Integration of Biomedical Atlases

Medical imaging in clinical analysis has been the subject of significant research for many years. In many cases scan images like CT scan and MRI scan may compliment physical examinations. Linking these scan images to biomedical atlases is fundamental to facilitate analysis. Biomedical atlas provides mapping between the graphical model and the ontology. Mapping from one atlas to another corresponding atlas is complex when it involves atlases from different model organisms. For example, having a general accepted nomenclature for the components of mouse embryo which is in parallel with the human atlas nomenclature provide an efficient means for analysis and modeling in biomedicine. However, this lead to interoperability issue. Therefore, taking the advantage of Semantic Web, Intelligent Agents and Ontology, this project starts with research linking imaging data of mouse embryo MRI to a standard canonical mouse atlas as designed in Edinburgh Mouse Atlas Project and also research on spatial rules to identify matching regions in atlases and images.

Acceleration of Early-Photon Fluorescence Molecular Tomography with Graphics Processing Units

Fluorescence molecular tomography (FMT) with early-photons can improve the spatial resolution and fidelity of the reconstructed results. However, its computing scale is always large which limits its applications. In this paper, we introduced an acceleration strategy for the early-photon FMT with graphics processing units (GPUs). According to the procedure, the whole solution of FMT was divided into several modules and the time consumption for each module is studied. In this strategy, two most time consuming modules (GdandWmodules) were accelerated with GPU, respectively, while the other modules remained coded in the Matlab. Several simulation studies with a heterogeneous digital mouse atlas were performed to confirm the performance of the acceleration strategy. The results confirmed the feasibility of the strategy and showed that the processing speed was improved significantly.