• Title/Summary/Keyword: F-X 필터

Search Result 22, Processing Time 0.018 seconds

Performance Characteristics of 3D GSO PET/CT Scanner (Philips GEMINI PET/DT) (3차원 GSO PET/CT 스캐너(Philips GEMINI PET/CT의 특성 평가)

  • Kim, Jin-Su;Lee, Jae-Sung;Lee, Byeong-Il;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
    • /
    • v.38 no.4
    • /
    • pp.318-324
    • /
    • 2004
  • Purpose: Philips GEMINI is a newly introduced whole-body GSO PET/CT scanner. In this study, performance of the scanner including spatial resolution, sensitivity, scatter fraction, noise equivalent count ratio (NECR) was measured utilizing NEMA NU2-2001 standard protocol and compared with performance of LSO, BGO crystal scanner. Methods: GEMINI is composed of the Philips ALLEGRO PET and MX8000 D multi-slice CT scanners. The PET scanner has 28 detector segments which have an array of 29 by 22 GSO crystals ($4{\times}6{\times}20$ mm), covering axial FOV of 18 cm. PET data to measure spatial resolution, sensitivity, scatter fraction, and NECR were acquired in 3D mode according to the NEMA NU2 protocols (coincidence window: 8 ns, energy window: $409[\sim}664$ keV). For the measurement of spatial resolution, images were reconstructed with FBP using ramp filter and an iterative reconstruction algorithm, 3D RAMLA. Data for sensitivity measurement were acquired using NEMA sensitivity phantom filled with F-18 solution and surrounded by $1{\sim}5$ aluminum sleeves after we confirmed that dead time loss did not exceed 1%. To measure NECR and scatter fraction, 1110 MBq of F-18 solution was injected into a NEMA scatter phantom with a length of 70 cm and dynamic scan with 20-min frame duration was acquired for 7 half-lives. Oblique sinograms were collapsed into transaxial slices using single slice rebinning method, and true to background (scatter+random) ratio for each slice and frame was estimated. Scatter fraction was determined by averaging the true to background ratio of last 3 frames in which the dead time loss was below 1%. Results: Transverse and axial resolutions at 1cm radius were (1) 5.3 and 6.5 mm (FBP), (2) 5.1 and 5.9 mm (3D RAMLA). Transverse radial, transverse tangential, and axial resolution at 10 cm were (1) 5.7, 5.7, and 7.0 mm (FBP), (2) 5.4, 5.4, and 6.4 mm (3D RAMLA). Attenuation free values of sensitivity were 3,620 counts/sec/MBq at the center of transaxial FOV and 4,324 counts/sec/MBq at 10 cm offset from the center. Scatter fraction was 40.6%, and peak true count rate and NECR were 88.9 kcps @ 12.9 kBq/mL and 34.3 kcps @ 8.84 kBq/mL. These characteristics are better than that of ECAT EXACT PET scanner with BGO crystal. Conclusion: The results of this field test demonstrate high resolution, sensitivity and count rate performance of the 3D PET/CT scanner with GSO crystal. The data provided here will be useful for the comparative study with other 3D PET/CT scanners using BGO or LSO crystals.

Applying Spitz Trace Interpolation Algorithm for Seismic Data (탄성파 자료를 이용한 Spitz 보간 알고리즘의 적용)

  • Yang Jung Ah;Suh Jung-Hee
    • Geophysics and Geophysical Exploration
    • /
    • v.6 no.4
    • /
    • pp.171-179
    • /
    • 2003
  • In land and marine seismic survey, we generally set receivers with equal interval suppose that sampling interval Is too narrow. But the cost of seismic data acquisition and that of data processing are much higher, therefore we should design proper receiver interval. Spatial aliasing can be occurred on seismic data when sampling interval is too coarse. If we Process spatial aliasing data, we can not obtain a good imaging result. Trace interpolation is used to improve the quality of multichannel seismic data processing. In this study, we applied the Spitz algorithm which is widely used in seismic data processing. This algorithm works well regardless of dip information of the complex underground structure. Using prediction filter and original traces with linear event we interpolated in f-x domain. We confirm our algorithm by examining for some synthetic data and marine data. After interpolation, we could find that receiver intervals get more narrow and the number of receiver is increased. We also could see that continuity of traces is more linear than before Applying this interpolation algorithm on seismic data with spatial aliasing, we may obtain a better migration imaging.