12451
Anirban Mukhopadhyay, Chul Woo Lim, Suchendra M. Bhandarkar, Hanbo Chen, Austin New, Tianming Liu, Khaled Rasheed, Thiab Taha
Localization of cortical regions of interests (ROIs) in the human brain via analysis of Diffusion Tensor Imaging (DTI) data plays a pivotal role in basic and clinical neuroscience. In recent studies, 358 common cortical landmarks in the human brain, termed as Dense Individualized and Common Connectivity-based Cortical Landmarks (DICCCOLs), have been identified. Each of these […]
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Shuai Li, Qinping Zhao, Shengfa Wang, Aimin Hao, Hong Qin
This paper articulates a novel method for the heterogeneous feature extraction and classification directly on volumetric images, which covers multi-scale point feature, multi-scale surface feature, multi-level curve feature, and blob feature. To tackle the challenge of complex volumetric inner structure and diverse feature forms, our technical solution hinges upon the integrated approach of locally-defined diffusion […]
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Tuomo Valkonen, Manfred Liebmann
We discuss the benefits, difficulties, and performance of a GPU implementation of the Chambolle-Pock algorithm for TGV (total generalised variation) denoising of medical diffusion tensor images. Whereas we have previously studied the denoising of 2D slices of $2 times 2$ and $3 times 3$ tensors, attaining satisfactory performance on a normal CPU, here we concentrate […]
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Andrei Frunza
An O(N^2) algorithm for computing hydrodynamic interaction (HI) in Brownian dynamics (BD) simulation has been implemented. A CPU and a GPU versions have been build, with the GPU one being tuned for performance, up to 40% of the maximum peak performance being obtained. The implementation was validated through simulations of diffusion polymers and comparisons of […]
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Evert van Aart, Neda Sepasian, Andrei Jalba, Anna Vilanova
Diffusion Tensor Imaging (DTI) allows to noninvasively measure the diffusion of water in fibrous tissue. By reconstructing the fibers from DTI data using a fiber-tracking algorithm, we can deduce the structure of the tissue. In this paper, we outline an approach to accelerating such a fiber-tracking algorithm using a Graphics Processing Unit (GPU). This algorithm, […]
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Wei Chen, Zi'ang Ding, Song Zhang, A. MacKay-Brandt, S. Correia, Huamin Qu, J.A. Crow, D.F. Tate, Zhicheng Yan, Qunsheng Peng
Visual exploration is essential to the visualization and analysis of densely sampled 3D DTI fibers in biological speciments, due to the high geometric, spatial, and anatomical complexity of fiber tracts. Previous methods for DTI fiber visualization use zooming, color-mapping, selection, and abstraction to deliver the characteristics of the fibers. However, these schemes mainly focus on […]
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T.H.J.M. Peeters, V. Prckovska, M. van Almsick, A. Vilanova, B.M. ter Haar Romeny
High angular resolution diffusion imaging (HARDI) is an emerging magnetic resonance imaging (MRI) technique that overcomes some decisive limitations of its predecessor diffusion tensor imaging (DTI). HARDI can resolve locally more than one direction in the diffusion pattern of water molecules and thereby opens up the opportunity to display and track crossing fibers. Showing the […]
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Won-Ki Jeong, P. Thomas Fletcher, Ran Tao, Ross T. Whitaker
In this paper we present a method to compute and visualize volumetric white matter connectivity in diffusion tensor magnetic resonance imaging (DT-MRI) using a Hamilton-Jacobi (H-J) solver on the GPU (graphics processing unit). Paths through the volume are assigned costs that are lower if they are consistent with the preferred diffusion directions. The proposed method […]
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Dorit Merhof, Markus Sonntag, Frank Enders, Christopher Nimsky, Peter Hastreiter, Gunther Greiner
Diffusion tensor imaging is of high value in neurosurgery, providing information about the location of white matter tracts in the human brain. For their reconstruction, streamline techniques commonly referred to as fiber tracking model the underlying fiber structures and have therefore gained interest. To meet the requirements of surgical planning and to overcome the visual […]
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Tim McGraw, Mariappan Nadar
We present a method for stochastic fiber tract mapping from diffusion tensor MRI (DT-MRI) implemented on graphics hardware. From the simulated fibers we compute a connectivity map that gives an indication of the probability that two points in the dataset are connected by a neuronal fiber path. A Bayesian formulation of the fiber model is […]
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