Interpolation of Orientation Distribution Functions (ODFs) in Q-ball Imaging

سال انتشار: 1391
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 984

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شناسه ملی سند علمی:

ICBME19_067

تاریخ نمایه سازی: 9 بهمن 1392

چکیده مقاله:

Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding directions is used and for reconstruction, the Q-ball method is applied. In this method, orientation distribution function (ODF) of fibers can be calculated. Mathematical models play a crucial role in the field of ODF. For instance, in registering Q-ball images for applications like group analysis or atlas construction, one needs to interpolate ODFs. To this end, principal diffusion directions (PDDs) of each ODF are needed. In this paper, PDDs are defined as vectors that connect the corresponding local maxima of ODF values. Then, ODFs are interpolated using PDDs. The proposed method is evaluated and compared with previous protocols. Experimental results show that the proposed interpolation algorithm preserves the principal direction of fiber tracts without producing any deviations in the tracts. It is shown that changes in the entropy of the interpolated ODFs are almost linear and the bloating effect (blurring of the principal directions) can be removed.

کلیدواژه ها:

high angular resolution diffusion imaging (HARDI) ، Q-ball imaging ، orientation distribution function (ODF) ، interpolation ، principal diffusion direction (PDD)

نویسندگان

Maryam Afzali

Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory (BiSIPL), Sharif University of Technology

Emad Fatemizadeh

Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory (BiSIPL), Sharif University of Technology

Hamid Soltanian-Zadeh

Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering University of Tehran, Tehran, Iran