A Novel Method to Improve Image Quality for 2-D Small Animal PET Reconstruction by Correcting a Monte Carlo-Simulated System Matrix Using an Artificial Neural Network

• Published in: IEEE transactions on nuclear science Vol. 56; no. 3; pp. 704 - 714
• Main Authors: Su, Kuan-Hao, Wu, Liang-Chih, Lee, Jih-Shian, Liu, Ren-Shyan, Chen, Jyh-Cheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2009; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Animals; Artificial neural network (ANN); Artificial neural networks; Computer simulation; Digital images; Image generation; Image quality; Image reconstruction; Imaging phantoms; Learning theory; Monte Carlo methods; Neural networks; PET reconstruction; Positron emission tomography; positron emission tomography (PET); Reconstruction; Samarium; small animal imaging; Stimulated emission; Studies; system matrix
• ISSN: 0018-9499; 1558-1578
• DOI: 10.1109/TNS.2009.2021267

The aim of this study was to improve image quality of statistical reconstruction by using the 2-D system matrix (SM) trained with an artificial neural network (ANN). For training the ANN SM (SM ANN ), the inputs of ANN, the digital images, were generated by scanning the mini-deluxe cold spot phantom at ten different orientations using an optical scanner (resolution: 0.01 mm/pixel). The desired outputs were generated by acquiring the projection data with the corresponding angles using the micro positron emission tomography (microPET) R4. In the ANN method, the ADALINE network with a bias vector and a momentum term were used. Moreover, a multiline-source phantom and a four-segment phantom were scanned to obtain the spatial resolutions and the quantitative accuracy for comparison, respectively. A rat FDG microPET image was acquired to compare the difference between the results reconstructed by the microPET's built-in 2-D-ordered subsets expectation maximization algorithm (OSEM), OSEM microPET , OSEM by Monte Carlo simulated SM, OSEM SMd , and OSEM by the SM ANN , OSEM ANN . In the multiline-source experiment, the resolutions of OSEM microPET measured at center, 10, and 20 mm from the center were 1.61, 1.78, and 2.30 mm, respectively. The resolutions of OSEM SMd and OSEM ANN were 1.24, 1.68, and 1.87, and 1.28, 1.62, and 1.72 mm, respectively. In the results of the four-segment phantom, the sum of absolute error of the truth versus the values reconstructed by OSEM microPET , OSEM SMd , and OSEM ANN were 1085.53, 913.48, and 435.02, respectively. By interpreting the results of the evaluation, the image quality reconstructed by the SM ANN is better than that reconstructed by the original SM. The results indicated that SM can be updated toward ideal SM using ANN for statistical reconstruction.