PETにおけるブロック型反復画像再構成法の定量的画質評価‐Dynamic RAMLA法とOSEM法の比較‐

  • 松本 圭一
    京都医療科学大学医療科学部放射線技術学科 大阪大学大学院医学系研究科保健学専攻医用物理工学講座
  • 北村 圭司
    株式会社島津製作所基盤技術研究所分子イメージングG
  • 清水 敬二
    先端医療センター分子イメージング研究グループ
  • 村瀬 研也
    大阪大学大学院医学系研究科保健学専攻医用物理工学講座

書誌事項

タイトル別名
  • Quantitative Evaluation of Block-iterative Reconstruction Image in PET: Comparison of the Dynamic RAMLA Algorithm and OSEM Algorithm
  • PETにおけるブロック型反復画像再構成法の定量的画質評価--Dynamic RAMLA法とOSEM法の比較
  • PET ニ オケル ブロックガタ ハンプク ガゾウ サイコウセイホウ ノ テイリョウテキ ガシツ ヒョウカ Dynamic RAMLAホウ ト OSEMホウ ノ ヒカク

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Purpose: Iterative reconstruction has been successfully used in whole-body PET imaging because of reductions in noise and scanning time. However, there are plural algorithms for image reconstruction such as OSEM, RAMLA and Dynamic RAMLA. Dynamic RAMLA (DRAMA) is an iterative algorithm similar to RAMLA, but the relaxation parameter is controlled in such a way that the propagation of noise from projection data to the reconstructed image. The purpose of this study was to investigate differences in the DRAMA and OSEM algorithms, in terms of real space and frequency space. Method: A whole-body torso phantom (NEMA image-quality phantom) filled with F-18 was scanned with a dedicated PET scanner. The smallest four spheres, with internal diameters of 10, 13, 17, and 22 mm, were filled with F-18 at an 8:1 concentration with respect to the background. The two largest spheres, with diameters of 28 and 37 mm, were not filled with water (empty). The emission scan for a 50 cm axial range varied from 5-20 minutes, to examine the effect of the count statistics on the quality of the reconstructed images. The images were reconstructed with OSEM by changing the number of subsets from 1 to 128 in each study. As to the number of iterations, both iterative reconstruction algorithms were one. As a reference standard, images with maximum counts (60 minutes) were reconstructed with a filtered-back projection method. The quality of the reconstructed images was evaluated in terms of contrast, background variability, and two-dimensional power spectrum analysis. Results: As for the real space results, OSEM with more than 32 subsets decreased contrast because of images with checkerboard noise. The DRAMA algorithm provided stable contrast even when count statistics were poor. A two-dimensional power spectrum analysis also revealed that the OSEM algorithm enhanced noise components in reconstruction with more than 32 subsets. Conclusion: Our preliminary data suggested that the OSEM algorithm requires few iterations with a small number of subsets for whole-body imaging. However, the DRAMA algorithm provides a reasonable signal-to-noise ratio with satisfactory spatial resolution even with one iteration. Especially in clinical whole-body PET, DRAMA was most useful because of its fast convergence and small computer burden.

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