EVALUATION OF MODIFIED FAST MARCHING ALGORITHM IN THE DETECTION OF FIBER CROSSING USING DIFFUSION TENSOR IMAGING DATA

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DARKI F.; AHMADIAN A.R.; SOLTANIANZADEH H.; ZAREEI MOJTABA; OGHABIAN M.A.

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Journal: IRANIAN JOURNAL OF MEDICAL PHYSICS Year:2007 | Volume:3 | Issue:13 Page(s): 1-16

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Title

EVALUATION OF MODIFIED FAST MARCHING ALGORITHM IN THE DETECTION OF FIBER CROSSING USING DIFFUSION TENSOR IMAGING DATA

Author(s)

Keywords

DIFFUSION TENSOR IMAGINGQ3

FIBER TRACTOGRAPHYQ3

FAST MARCHINGQ3

ADAPTIVE FRACTIONAL ANISOTROPY WEIGHTED FACTORQ3

FIBER CROSSINGQ3

Abstract

Introduction: DIFFUSION TENSOR IMAGING (DTI) is a non- invasive tool for estimating the diffusion of water molecules in white matter tracts. In this method, a second order tensor is assigned to each voxel. The principal eigenvector of each tensor determines the diffusion direction in the voxel. White matter fiber tracking algorithms reconstruct three dimensional pathways using the vector field of DTI dataset. Material and Methods: FAST MARCHING algorithm is a useful method for FIBER TRACTOGRAPHY in which the co-linearity of principal eigenvectors determines the speed of diffusion. In this research, the speed function has been modified. The proposed speed function has an ADAPTIVE FRACTIONAL ANISOTROPY WEIGHTED FACTOR which can set the speed according to brain environment (isotropic and non-isotropic).Results: By this modification, the algorithm can extract the fiber voxels with high accuracy. This method has high performance in FIBER CROSSING detection. The ability of the modified algorithm in the presence of different noise levels has been assessed and it is shown that the proposed algorithm is robust in the presence of noise.Discussion and Conclusion: In the modified algorithm, the eigenvalues have been considered in the adaptive weighted factor. This factor changes the speed value adaptively according to brain environment. By this modification, the diffusion front can be entered into the crossing regions because FA threshold is not considered in this algorithm. Eliminating the FA threshold leads to increasing the time of tractography by a factor of almost two and half. Additionally, the algorithm becomes robust in comparison to noise because for high FA value the effect of noise is reduced.

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APA: Copy

DARKI, F., AHMADIAN, A.R., SOLTANIANZADEH, H., ZAREEI, MOJTABA, & OGHABIAN, M.A.. (2007). EVALUATION OF MODIFIED FAST MARCHING ALGORITHM IN THE DETECTION OF FIBER CROSSING USING DIFFUSION TENSOR IMAGING DATA. IRANIAN JOURNAL OF MEDICAL PHYSICS, 3(13), 1-16. SID. https://sid.ir/paper/96926/en

Vancouver: Copy

DARKI F., AHMADIAN A.R., SOLTANIANZADEH H., ZAREEI MOJTABA, OGHABIAN M.A.. EVALUATION OF MODIFIED FAST MARCHING ALGORITHM IN THE DETECTION OF FIBER CROSSING USING DIFFUSION TENSOR IMAGING DATA. IRANIAN JOURNAL OF MEDICAL PHYSICS[Internet]. 2007;3(13):1-16. Available from: https://sid.ir/paper/96926/en

IEEE: Copy

F. DARKI, A.R. AHMADIAN, H. SOLTANIANZADEH, MOJTABA ZAREEI, and M.A. OGHABIAN, “EVALUATION OF MODIFIED FAST MARCHING ALGORITHM IN THE DETECTION OF FIBER CROSSING USING DIFFUSION TENSOR IMAGING DATA,” IRANIAN JOURNAL OF MEDICAL PHYSICS, vol. 3, no. 13, pp. 1–16, 2007, [Online]. Available: https://sid.ir/paper/96926/en

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