The Software Development for Diffusion Tensor Imaging

  • Song, In-Chan (Department of Radiology, Seoul National University Hospital) ;
  • Chang, Kee-Hyun (Department of Radiology, Seoul National University Hospital) ;
  • Han, Moon-Hee (Department of Radiology, Seoul National University Hospital)
  • Published : 2001.11.01

Abstract

Purpose: We developed the software for diffusion tensor imaging and evaluated its feasibility in norm brains. Method: Five normal volunteers, aged from 25 to 29 years, were examined on a 1.5 T MR system. the diffusion tensor pulse sequence used a SE-EPI with 6 diffusion gradie directions of (1, 1, 0), (-1, 1,0), (1, 0, 1), (-1, 0, 1), (0, 1, 1), (0, 1, -1) and also with no diffusion gradient. A b-factor of 500 sec/mm2 was used. Measurement parameter were as follows; TR/TE=10000 ms/99 ms, FOV=240 mm, matrix=128$\times$128, slice thickness/gap=6 mm/0 mm, bandwidth=91 kHz and the number of total slices=20. Four repeated axial diffusion images were averaged for diffusion tensor imaging. A total scan 11 of 4 min 30 sec was used. Six full diffusion tensor components of Dxx, Dyy, Dzz, Dxy, Dxz and Dyz were obtained using two-point linear regression model from 7 diffusion-weight images at each pixel and fractional anisotropy and lattice index images was estimated fr their eigenvectors and eigenvalues. Our program was written on a platform of IDL. W evaluated the qualities of fractional anisotropy and lattice index images of normal brains a knew whether our software for diffusion tensor imaging may be feasible.

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