Name
Abstract | ||
|---|---|---|
While the performance of small animal PET systems has been improved impressively in terms of spatial resolution and sensitivity, demands for further improvements remain high with growing number of applications. Here we propose a novel PET system design that integrates a high-resolution detector into an existing PET system to obtain higher-resolution images in a target region. The high-resolution detector will be adaptively positioned based on the detectability or quantitative accuracy of a feature of interest. The proposed system will be particularly effective for studying human cancers using animal models where tumors are often grown near the skin surface and therefore permit close contact with the high resolution detector. It will also be useful for the high-resolution brain imaging in rodents. In this paper, we present the theoretical analysis and Monte Carlo simulation studies of the performance of the proposed system. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02498-6_3 | IPMI |
Keywords | Field | DocType |
existing pet system,high resolution detector,high-resolution brain imaging,high-resolution adaptive pet imaging,animal model,small animal pet system,spatial resolution,novel pet system design,monte carlo simulation study,proposed system,high-resolution detector,monte carlo simulation,system design,high resolution,brain imaging | Computer vision,Monte Carlo method,Pattern recognition,Computer science,Systems design,Artificial intelligence,Neuroimaging,Image resolution,Detector | Conference |
Volume | ISSN | Citations |
21 | 1011-2499 | 1 |
PageRank | References | Authors |
0.36 | 11 | 2 |