System matrix for OSEM SPECT with attenuation compensation in mesh domain

The purpose of this study was to develop and implement an accurate and computationally efficient method for determination of the mesh-domain ssssssystem matrix including attenuation compensation for Ordered Subsets Expectation Maximization (OSEM) Single Photon Emission Computed Tomography (SPECT). The mesh-domain system matrix elements were estimated by first partitioning the object domain into strips parallel to detector face and with width not exceeding the size of a detector unit. This was followed by approximating the integration over the strip/mesh-element union. This approximation is product of: (i) strip width, (ii) intersection length of a ray central to strip with a mesh element, and (iii) the response and expansion function evaluated at midpoint of the intersection length. Reconstruction was performed using OSEM without regularization and with exact knowledge of the attenuation map. The method was evaluated using synthetic SPECT data generated using SIMIND Monte Carlo simulation software. Comparative quantitative and qualitative analysis included: bias, variance, standard deviation and line-profiles within three different regions of interest. We found that no more than two divisions per detector bin were needed for good quality reconstructed images when using a high resolution mesh.

[1]  William Paul Segars,et al.  Development of a new dynamic NURBS-based cardiac-torso (NCAT) phantom , 2001 .

[3]  Ronald H. Huesman,et al.  Tomographic reconstruction using an adaptive tetrahedral mesh defined by a point cloud , 2006, IEEE Transactions on Medical Imaging.

[4]  R.G. Delgado,et al.  Mesh model based projection operator for emission tomography , 2007, 2007 IEEE Nuclear Science Symposium Conference Record.

[5]  Yongyi Yang,et al.  Content-adaptive 3D mesh modeling for representation of volumetric images , 2002, Proceedings. International Conference on Image Processing.

[6]  Yongyi Yang,et al.  Tomographic image reconstruction based on a content-adaptive mesh model , 2004, IEEE Transactions on Medical Imaging.

[7]  Yongyi Yang,et al.  Tomographic image reconstruction using content-adaptive mesh modeling , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).