A Novel Framework for repeated measurements in diffusion tensor imaging

• In the context of diffusion tensor imaging (DTI), the utility of making repeated measurements in each diffusion sensitizing direction has been the subject of numerous stud-ies. One can estimate the true signal value using either the raw complex-valued data or the real-valued magnitudesignal. While conventional methods focus on the former strategy, this paper proposes a new framework for acquiring/processing repeated measurements based on the latter strategy. The aim is to enhance the DTI processing pipeline by adding a diffusion signal estimator (DSE). This permits us to exploit the knowledge of the noise distribution to estimate the true signal value in each direction. An extensive study of the proposed framework, including theoretical analysis, experiments with synthetic data, performance evaluation and comparisons is presented.Our results show that the precision of estimated diffusionparameters is dependent on the number of available samplesand the manner in which the DSE accounts for noise. Theproposed framework improves the precision in estimationof diffusion parameters given a sufficient number of uniquemeasurements. This encourages future work with rich realdatasets and downstream applications.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Medical Engineering -- Medical Image Processing (hsv//eng)

Nyckelord

Repeated measurements

Rician noise

Tensor estimation

Diffusion signal estimation

Diffusion-weighted MRI

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