| 1. |
- Fang, Chengran, et al.
(författare)
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Diffusion MRI simulation of realistic neurons with SpinDoctor and the Neuron Module
- 2020
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Ingår i: NeuroImage. - : Academic Press Inc.. - 1053-8119 .- 1095-9572. ; 222
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Tidskriftsartikel (refereegranskat)abstract
- The diffusion MRI signal arising from neurons can be numerically simulated by solving the Bloch-Torrey partial differential equation. In this paper we present the Neuron Module that we implemented within the Matlab-based diffusion MRI simulation toolbox SpinDoctor. SpinDoctor uses finite element discretization and adaptive time integration to solve the Bloch-Torrey partial differential equation for general diffusion-encoding sequences, at multiple b-values and in multiple diffusion directions. In order to facilitate the diffusion MRI simulation of realistic neurons by the research community, we constructed finite element meshes for a group of 36 pyramidal neurons and a group of 29 spindle neurons whose morphological descriptions were found in the publicly available neuron repository NeuroMorpho.Org. These finite elements meshes range from having 15,163 nodes to 622,553 nodes. We also broke the neurons into the soma and dendrite branches and created finite elements meshes for these cell components. Through the Neuron Module, these neuron and cell components finite element meshes can be seamlessly coupled with the functionalities of SpinDoctor to provide the diffusion MRI signal attributable to spins inside neurons. We make these meshes and the source code of the Neuron Module available to the public as an open-source package. To illustrate some potential uses of the Neuron Module, we show numerical examples of the simulated diffusion MRI signals in multiple diffusion directions from whole neurons as well as from the soma and dendrite branches, and include a comparison of the high b-value behavior between dendrite branches and whole neurons. In addition, we demonstrate that the neuron meshes can be used to perform Monte-Carlo diffusion MRI simulations as well. We show that at equivalent accuracy, if only one gradient direction needs to be simulated, SpinDoctor is faster than a GPU implementation of Monte-Carlo, but if many gradient directions need to be simulated, there is a break-even point when the GPU implementation of Monte-Carlo becomes faster than SpinDoctor. Furthermore, we numerically compute the eigenfunctions and the eigenvalues of the Bloch-Torrey and the Laplace operators on the neuron geometries using a finite elements discretization, in order to give guidance in the choice of the space and time discretization parameters for both finite elements and Monte-Carlo approaches. Finally, we perform a statistical study on the set of 65 neurons to test some candidate biomakers that can potentially indicate the soma size. This preliminary study exemplifies the possible research that can be conducted using the Neuron Module.
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| 2. |
- Forsberg, Daniel, et al.
(författare)
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Improving Registration Using Multi-channel Diffeomorphic Demons Combined with Certainty Maps
- 2011
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Ingår i: Multimodal Brain Image Analysis. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642244452 ; , s. 19-26
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Konferensbidrag (refereegranskat)abstract
- The number of available imaging modalities increases both in clinical practice and in clinical studies. Even though data from multiple modalities might be available, image registration is typically only performed using data from a single modality. In this paper, we propose using certainty maps together with multi-channel diffeomorphic demons in order to improve both accuracy and robustness when performing image registration. The proposed method is evaluated using DTI data, multiple region overlap measures and a fiber bundle similarity metric.
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| 3. |
- Menon, Vinod, et al.
(författare)
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Microstructural organization of human insula is linked to its macrofunctional circuitry and predicts cognitive control
- 2020
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Ingår i: eLife. - : eLife Sciences Publications, Ltd. - 2050-084X. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- The human insular cortex is a heterogeneous brain structure which plays an integrative role in guiding behavior. The cytoarchitectonic organization of the human insula has been investigated over the last century using postmortem brains but there has been little progress in noninvasive in vivo mapping of its microstructure and large-scale functional circuitry. Quantitative modeling of multi-shell diffusion MRI data from 413 participants revealed that human insula microstructure differs significantly across subdivisions that serve distinct cognitive and affective functions. Insular microstructural organization was mirrored in its functionally interconnected circuits with the anterior cingulate cortex that anchors the salience network, a system important for adaptive switching of cognitive control systems. Furthermore, insular microstructural features, confirmed in Macaca mulatta, were linked to behavior and predicted individual differences in cognitive control ability. Our findings open new possibilities for probing psychiatric and neurological disorders impacted by insular cortex dysfunction, including autism, schizophrenia, and fronto-temporal dementia.
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| 4. |
- Nguyen, Van Dang, 1985-, et al.
(författare)
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Diffusion MRI simulation of realistic neurons with SpinDoctor and the Neuron Module
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The diffusion MRI signal arising from neurons can be numerically simulated by solving the Bloch- Torrey partial differential equation. In this paper we present the Neuron Module that we imple- mented within the Matlab-based diffusion MRI simulation toolbox SpinDoctor. SpinDoctor uses finite element discretization and adaptive time integration to solve the Bloch-Torrey partial dif- ferential equation for general diffusion-encoding sequences, at multiple b-values and in multiple diffusion directions.In order to facilitate the diffusion MRI simulation of realistic neurons by the research community, we constructed finite element meshes for a group of 36 pyramidal neurons and a group of 29 spindle neurons whose morphological descriptions were found in the publicly available neuron repositoryNeuroMorpho.Org. These finite elements meshes range from having 15163 nodes to 622553 nodes. We also broke the neurons into the soma and dendrite branches and created finite elements meshes for these cell components. Through the Neuron Module, these neuron and components finite element meshes can be seamlessly coupled with the functionalities of SpinDoctor to provide the diffusion MRI signal attributable to spins inside neurons. We make these meshes and the source code of the Neuron Module available to the public as an open-source package.To illustrate some potential uses of the Neuron Module, we show numerical examples of the simu- lated dMRI signals in multiple diffusion directions from whole neurons as well as from the soma and dendrite branches, include a comparison of the high b-value behavior between dendrite branches and whole neurons.
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| 5. |
- Nguyen, Van Dang, 1985-, et al.
(författare)
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Portable simulation framework for diffusion MRI
- 2019
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Ingår i: Journal of magnetic resonance. - : Academic Press. - 1090-7807 .- 1096-0856. ; 309
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Tidskriftsartikel (refereegranskat)abstract
- The numerical simulation of the diffusion MRI signal arising from complex tissue micro-structures is helpful for understanding and interpreting imaging data as well as for designing and optimizing MRI sequences. The discretization of the Bloch-Torrey equation by finite elements is a more recently developed approach for this purpose, in contrast to random walk simulations, which has a longer history. While finite elements discretization is more difficult to implement than random walk simulations, the approach benefits from a long history of theoretical and numerical developments by the mathematical and engineering communities. In particular, software packages for the automated solutions of partial differential equations using finite elements discretization, such as FEniCS, are undergoing active support and development. However, because diffusion MRI simulation is a relatively new application area, there is still a gap between the simulation needs of the MRI community and the available tools provided by finite elements software packages. In this paper, we address two potential difficulties in using FEniCS for diffusion MRI simulation. First, we simplified software installation by the use of FEniCS containers that are completely portable across multiple platforms. Second, we provide a portable simulation framework based on Python and whose code is open source. This simulation framework can be seamlessly integrated with cloud computing resources such as Google Colaboratory notebooks working on a web browser or with Google Cloud Platform with MPI parallelization. We show examples illustrating the accuracy, the computational times, and parallel computing capabilities. The framework contributes to reproducible science and open-source software in computational diffusion MRI with the hope that it will help to speed up method developments and stimulate research collaborations.
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| 6. |
- Ravikumar, Sadhana, et al.
(författare)
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Improved Segmentation of Deep Sulci in Cortical Gray Matter Using a Deep Learning Framework Incorporating Laplace’s Equation
- 2023
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Ingår i: Information Processing in Medical Imaging - 28th International Conference, IPMI 2023, Proceedings. - 1611-3349 .- 0302-9743. - 9783031340475 ; 13939 LNCS, s. 692-704
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Konferensbidrag (refereegranskat)abstract
- When developing tools for automated cortical segmentation, the ability to produce topologically correct segmentations is important in order to compute geometrically valid morphometry measures. In practice, accurate cortical segmentation is challenged by image artifacts and the highly convoluted anatomy of the cortex itself. To address this, we propose a novel deep learning-based cortical segmentation method in which prior knowledge about the geometry of the cortex is incorporated into the network during the training process. We design a loss function which uses the theory of Laplace’s equation applied to the cortex to locally penalize unresolved boundaries between tightly folded sulci. Using an ex vivo MRI dataset of human medial temporal lobe specimens, we demonstrate that our approach outperforms baseline segmentation networks, both quantitatively and qualitatively.
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| 7. |
- Wassermann, Demian, et al.
(författare)
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Sensing Spindle Neurons in the Insula with Multi-shell Diffusion MRI
- 2018
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Konferensbidrag (refereegranskat)abstract
- Sensing microstructural characteristics of human brain tissue with clinical scanners has been an area of heated debate in the diffusion MRI (dMRI) community. In this work, we propose that diffusion MRI on clinical scanners is sensitive to the presence of spindle neurons.Spindle neurons, located in the insular and anterior cingular cortices, are only present in mammals with high cognitive functions. Albeit this neurons' role is not yet known, evidence suggests they facilitate rapid long-range information integration.In this work, we provide theoretical and in-silico evidence that the dMRI signal is sensitive to the presence of spindle neurons as well as preliminary evidence on human dMRI images.
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