| 1. |
- Granlund, Gösta H., et al.
(författare)
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Biological Vision
- 1995
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Ingår i: Signal Processing for Computer Vision. - Dordrecht : Kluwer. - 0792395301 - 9780792395300 ; , s. 41-95
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Bokkapitel (refereegranskat)abstract
- This chapter givesan overview of important biological vision mechanisms. Although agreat deal is known about neural processing of visual information,most essential questions about biological vision remain as yetunanswered. Nonetheless, the knowledge available has already provideduseful guidance to the organization of effective machine visionsystems.
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| 2. |
- Karlholm, Jörgen, et al.
(författare)
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Object Tracking Based on the Orientation Tensor Concept
- 1994
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We apply the 3D-orientation tensor representation to construct an object tracking algorithm. 2D-line normal flow is estimated by computing the eigenvector associated with the largest eigenvalue of 3D (two spatial dimensions plus time) tensors with a planar structure. Object's true 2D velocity is computed by averaging tensors with consistent normal flows, generating a 3D line representation that corresponds to a 2D point in motion. Flow induced by camera rotation is compensated for by ignoring points with velocity consistent with the ego-rotation. A region-of-interest growing process based on motion consistency generates estimates of object size and position.
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| 3. |
- Karlholm, Jörgen, et al.
(författare)
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Object Tracking Based on the Orientation Tensor Concept
- 1995
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Ingår i: Theory and Applications of Image Analysis II. - Singapore : World Scientific Publishing. - 9810224486 ; , s. 267-278
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Bokkapitel (populärvet., debatt m.m.)abstract
- We apply the 3D-orientation tensor representation to construct an object tracking algorithm. 2D-line normal flow is estimated by computing the eigenvector associated with the largest eigenvalue of 3D (two spatial dimensions plus time) tensors with a planar structure. Object's true 2D velocity is computed by averaging tensors with consistent normal flows, generating a 3D line represention that corresponds to a 2D point in motion. Flow induced by camera rotation is compensated for by ignoring points with velocity consistent with the ego-rotation. A region-of-interest growing process based on motion consistency generates estimates of object size and position. Introduction The literature on optical flow estimation is wast. Descriptions and performance studies of a number of different techniques are given in and the monographs by Fleet and Jahne. We will only briefly describe the particular methods used in the present study. Details on the tensor field represention a...
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| 4. |
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| 5. |
- Nilsson, Markus, et al.
(författare)
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Mapping prostatic microscopic anisotropy using linear and spherical b-tensor encoding : A preliminary study
- 2021
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 86:4, s. 2025-2033
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Tensor-valued diffusion encoding provides more specific information than conventional diffusion-weighted imaging (DWI), but has mainly been applied in neuroimaging studies. This study aimed to assess its potential for the imaging of prostate cancer (PCa). Methods: Seventeen patients with histologically proven PCa were enrolled. DWI of the prostate was performed with linear and spherical tensor encoding using a maximal b-value of 1.5 ms/µm2 and a voxel size of 3 × 3 × 4 mm3. The gamma-distribution model was used to estimate the mean diffusivity (MD), the isotropic kurtosis (MKI), and the anisotropic kurtosis (MKA). Regions of interest were placed in MR-defined cancerous tissues, as well as in apparently healthy tissues in the peripheral and transitional zones (PZs and TZs). Results: DWI with linear and spherical encoding yielded different image contrasts at high b-values, which enabled the estimation of MKA and MKI. Compared with healthy tissue (PZs and TZs combined) the cancers displayed a significantly lower MD (P <.05), higher MKI (P < 10−5), and lower MKA (P <.05). Compared with the TZ, tissue in the PZ showed lower MD (P < 10−3) and higher MKA (P < 10−3). No significant differences were found between cancers of different Gleason scores, possibly because of the limited sample size. Conclusion: Tensor-valued diffusion encoding enabled mapping of MKA and MKI in the prostate. The elevated MKI in PCa compared with normal tissues suggests an elevated heterogeneity in the cancers. Increased in-plane resolution could improve tumor delineation in future studies.
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| 6. |
- Shemesh, Noam, et al.
(författare)
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Conventions and nomenclature for double diffusion encoding NMR and MRI.
- 2016
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 75:1, s. 82-87
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Forskningsöversikt (refereegranskat)abstract
- Stejskal and Tanner's ingenious pulsed field gradient design from 1965 has made diffusion NMR and MRI the mainstay of most studies seeking to resolve microstructural information in porous systems in general and biological systems in particular. Methods extending beyond Stejskal and Tanner's design, such as double diffusion encoding (DDE) NMR and MRI, may provide novel quantifiable metrics that are less easily inferred from conventional diffusion acquisitions. Despite the growing interest on the topic, the terminology for the pulse sequences, their parameters, and the metrics that can be derived from them remains inconsistent and disparate among groups active in DDE. Here, we present a consensus of those groups on terminology for DDE sequences and associated concepts. Furthermore, the regimes in which DDE metrics appear to provide microstructural information that cannot be achieved using more conventional counterparts (in a model-free fashion) are elucidated. We highlight in particular DDE's potential for determining microscopic diffusion anisotropy and microscopic fractional anisotropy, which offer metrics of microscopic features independent of orientation dispersion and thus provide information complementary to the standard, macroscopic, fractional anisotropy conventionally obtained by diffusion MR. Finally, we discuss future vistas and perspectives for DDE. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.
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| 7. |
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| 8. |
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| 9. |
- Westelius, Carl-Johan, et al.
(författare)
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Phase-based Disparity Estimation
- 1995
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Ingår i: Vision as Process. - Berlin : Springer-Verlag. - 354058143X - 038758143X ; , s. 157-178
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The problem of estimating depth information from two or more images of a scene is one which has received considerable attention over the years and a wide variety of methods have been proposed to solve it [Barnard and Fichsler, 1982; Fleck, 1991]. Methods based on correlation and methods using some form of feature matching between the images have found most widespread use. Of these, the latter have attracted increasing attention since the work of Marr [Marr, 1982], in which the features are zero-crossings on varying scales. These methods share an underlying basis of spatial domain operations.In recent years, however, increasing interest has been shown in computational models of vision based primarily on a localized frequency domain representation - the Gabor representation [Gabor, 1946; Adelson and Bergen, 1985], first suggested in the context of computer vision by Granlund [Granlund, 1978].
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| 10. |
- Westelius, Carl-Johan, et al.
(författare)
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Prototyping, Visualization and Simulation Using the Application Visualization System
- 1994
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Ingår i: Experimental Environments for Computer Vision and Image Processing. - Singapore : World Scientific Publishing Co. Pte. Ltd.. - 981021510X ; , s. 33-62
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The Application Visualization System software from Advanced Visual Systems Inc is an interactive visualization environment for scientists, engineers and technical professionals. This report contains a short overview of the AVS software packages and a discussion about its general performance. The software package has actively been used at the Computer Vision Laboratory, Linköping University, during the last three years. The AVS package has been used in many applications. Examples are generating images from a virtual environment, simulation of a controllable robot with a stereo camera head and visualization of multidimensional data structures. Lately we also have used AVS for handling communication between different processes which may be distributed on different machines. AVS was primarily developed as a tool for visualization of complex data sets. However, another important aspect of the software is that it can be used as an advanced workbench for controlling networks of Unix processes (including external ones on different machine types) using simple visual programming.
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| 11. |
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| 12. |
- Westin, Carl-Fredrik, et al.
(författare)
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Attention Control for Robot Vision
- 1996
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Ingår i: CVPR. - : IEEE Computer Society Press. ; , s. 726-733
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Konferensbidrag (refereegranskat)
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| 13. |
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| 14. |
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| 17. |
- Abramian, David, 1992-, et al.
(författare)
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Diffusion-Informed Spatial Smoothing of fMRI Data in White Matter Using Spectral Graph Filters
- 2021
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Ingår i: NeuroImage. - : Elsevier. - 1053-8119 .- 1095-9572. ; 237
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Tidskriftsartikel (refereegranskat)abstract
- Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detachability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject’s unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project’s 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.
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| 18. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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Prediction from off-grid samples using continuous normalized convolution
- 2007
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 87:3, s. 353-365
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.
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| 19. |
- Behjat, Hamid, et al.
(författare)
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Characterization of Spatial Dynamics of Fmri Data in White Matter Using Diffusion-Informed White Matter Harmonics
- 2021
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Ingår i: 2021 IEEE 18th International Symposium On Biomedical Imaging (ISBI). - : Institute of Electrical and Electronics Engineers (IEEE). - 1945-7928 .- 1945-8452. - 9781665412469 - 9781665429474
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Konferensbidrag (refereegranskat)abstract
- In this work, we leverage the Laplacian eigenbasis of voxelwise white matter (WM) graphs derived from diffusionweighted MRI data, dubbed WM harmonics, to characterize the spatial structure of WM fMRI data. Our motivation for such a characterization is based on studies that show WM fMRI data exhibit a spatial correlational anisotropy that coincides with underlying fiber patterns. By quantifying the energy content of WM fMRI data associated with subsets of WM harmonics across multiple spectral bands, we show that the data exhibits notable subtle spatial modulations under functional load that are not manifested during rest. WM harmonics provide a novel means to study the spatial dynamics of WM fMRI data, in such way that the analysis is informed by the underlying anatomical structure.
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| 20. |
- Brabec, Jan, et al.
(författare)
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Histogram analysis of tensor-valued diffusion MRI in meningiomas : Relation to consistency, histological grade and type
- 2022
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Ingår i: NeuroImage: Clinical. - : Elsevier BV. - 2213-1582. ; 33
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Preoperative radiological assessment of meningioma characteristics is of value for pre- and post-operative patient management, counselling, and surgical approach.PURPOSE: To investigate whether tensor-valued diffusion MRI can add to the preoperative prediction of meningioma consistency, grade and type.MATERIALS AND METHODS: 30 patients with intracranial meningiomas (22 WHO grade I, 8 WHO grade II) underwent MRI prior to surgery. Diffusion MRI was performed with linear and spherical b-tensors with b-values up to 2000 s/mm2. The data were used to estimate mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and its components-the anisotropic and isotropic kurtoses (MKA and MKI). Meningioma consistency was estimated for 16 patients during resection based on ultrasonic aspiration intensity, ease of resection with instrumentation or suction. Grade and type were determined by histopathological analysis. The relation between consistency, grade and type and dMRI parameters was analyzed inside the tumor ("whole-tumor") and within brain tissue in the immediate periphery outside the tumor ("rim") by histogram analysis.RESULTS: Lower 10th percentiles of MK and MKA in the whole-tumor were associated with firm consistency compared with pooled soft and variable consistency (n = 7 vs 9; U test, p = 0.02 for MKA 10 and p = 0.04 for MK10) and lower 10th percentile of MD with variable against soft and firm (n = 5 vs 11; U test, p = 0.02). Higher standard deviation of MKI in the rim was associated with lower grade (n = 22 vs 8; U test, p = 0.04) and in the MKI maps we observed elevated rim-like structure that could be associated with grade. Higher median MKA and lower median MKI distinguished psammomatous type from other pooled meningioma types (n = 5 vs 25; U test; p = 0.03 for MKA 50 and p = 0.03 and p = 0.04 for MKI 50).CONCLUSION: Parameters from tensor-valued dMRI can facilitate prediction of consistency, grade and type.
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| 21. |
- Brabec, Jan, et al.
(författare)
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Separating Glioma Hyperintensities From White Matter by Diffusion-Weighted Imaging With Spherical Tensor Encoding
- 2022
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Ingår i: Frontiers in Neuroscience. - : Frontiers Media SA. - 1662-4548 .- 1662-453X. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- Background: Tumor-related hyperintensities in high b-value diffusion-weighted imaging (DWI) are radiologically important in the workup of gliomas. However, the white matter may also appear as hyperintense, which may conflate interpretation.Purpose: To investigate whether DWI with spherical b-tensor encoding (STE) can be used to suppress white matter and enhance the conspicuity of glioma hyperintensities unrelated to white matter.Materials and Methods: Twenty-five patients with a glioma tumor and at least one pathology-related hyperintensity on DWI underwent conventional MRI at 3 T. The DWI was performed both with linear and spherical tensor encoding (LTE-DWI and STE-DWI). The LTE-DWI here refers to the DWI obtained with conventional diffusion encoding and averaged across diffusion-encoding directions. Retrospectively, the differences in contrast between LTE-DWI and STE-DWI, obtained at a b-value of 2,000 s/mm2, were evaluated by comparing hyperintensities and contralateral normal-appearing white matter (NAWM) both visually and quantitatively in terms of the signal intensity ratio (SIR) and contrast-to-noise ratio efficiency (CNReff).Results: The spherical tensor encoding DWI was more effective than LTE-DWI at suppressing signals from white matter and improved conspicuity of pathology-related hyperintensities. The median SIR improved in all cases and on average by 28%. The median (interquartile range) SIR was 1.9 (1.6 - 2.1) for STE and 1.4 (1.3 - 1.7) for LTE, with a significant difference of 0.4 (0.3 -0.5) (p < 10-4, paired U-test). In 40% of the patients, the SIR was above 2 for STE-DWI, but with LTE-DWI, the SIR was below 2 for all patients. The CNReff of STE-DWI was significantly higher than of LTE-DWI: 2.5 (2 - 3.5) vs. 2.3 (1.7 - 3.1), with a significant difference of 0.4 (-0.1 -0.6) (p < 10-3, paired U-test). The STE improved CNReff in 70% of the cases. We illustrate the benefits of STE-DWI in three patients, where STE-DWI may facilitate an improved radiological description of tumor-related hyperintensity, including one case that could have been missed out if only LTE-DWI was inspected.Conclusion: The contrast mechanism of high b-value STE-DWI results in a stronger suppression of white matter than conventional LTE-DWI, and may, therefore, be more sensitive and specific for assessment of glioma tumors and DWI-hyperintensities.
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| 22. |
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| 23. |
- Brun, Anders, 1976-, et al.
(författare)
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A tensor-like representation for averaging, filtering and interpolation of 3D object orientation data
- 2005
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Ingår i: Image Processing, 2005. ICIP 2005. IEEE International Conference on (Volume:3 ). - 0780391349 ; , s. 1092-1095
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Konferensbidrag (refereegranskat)abstract
- Averaging, filtering and interpolation of 3-D object orientation data is important in both computer vision and computer graphics, for instance to smooth estimates of object orientation and interpolate between keyframes in computer animation. In this paper we present a novel framework in which the non-linear nature of these problems is avoided by embedding the manifold of 3-D orientations into a 16-dimensional Euclidean space. Linear operations performed in the new representation can be shown to be rotation invariant, and defining a projection back to the orientation manifold results in optimal estimates with respect to the Euclidean metric. In other words, standard linear filters, interpolators and estimators may be applied to orientation data, without the need for an additional machinery to handle the non-linear nature of the problems. This novel representation also provides a way to express uncertainty in 3-D orientation, analogous to the well known tensor representation for lines and hyperplanes.
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| 24. |
- Brun, Anders, 1976-, et al.
(författare)
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Clustering Fiber Traces Using Normalized Cuts
- 2004
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Ingår i: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540229766 - 9783540301356 ; , s. 368-375
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to create a weighted undirected graph which is partitioned into coherent sets using the normalized cut (Ncut) criterion. A simple and yet effective method for pairwise comparison of fiber traces is presented which in combination with the Ncut criterion is shown to produce plausible segmentations of both synthetic and real fiber trace data. Segmentations are visualized as colored stream-tubes or transformed to a segmentation of voxel space, revealing structures in a way that looks promising for future explorative studies of diffusion weighted MRI data.
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| 25. |
- Brun, Anders, 1976-, et al.
(författare)
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Coloring of DT-MRI fiber traces using Laplacian Eigenmaps
- 2003
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Ingår i: Computer Aided Systems Theory - EUROCAST 2003. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540202219 - 9783540452102 ; , s. 518-529
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Konferensbidrag (refereegranskat)abstract
- We propose a novel post processing method for visualization of fiber traces from DT-MRI data. Using a recently proposed non-linear dimensionality reduction technique, Laplacian eigenmaps [3], we create a mapping from a set of fiber traces to a low dimensional Euclidean space. Laplacian eigenmaps constructs this mapping so that similar traces are mapped to similar points, given a custom made pairwise similarity measure for fiber traces. We demonstrate that when the low-dimensional space is the RGB color space, this can be used to visualize fiber traces in a way which enhances the perception of fiber bundles and connectivity in the human brain.
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