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Curve interpolation model for visualising disjointed neural elements.

Rahim MS, Razzali N, Sunar MS, Altameem A, Rehman A - Neural Regen Res (2012)

Bottom Line: Existing neuron models have been found to be defective in the aspect of realism.Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism.The result shows about 82% acceptance and satisfaction rate.

View Article: PubMed Central - PubMed

Affiliation: UTMViCubeLab, Department of Computer Graphics and Multimedia, FSKSM, University of Technology, Skudai 81310, Malaysia.

ABSTRACT
Neuron cell are built from a myriad of axon and dendrite structures. It transmits electrochemical signals between the brain and the nervous system. Three-dimensional visualization of neuron structure could help to facilitate deeper understanding of neuron and its models. An accurate neuron model could aid understanding of brain's functionalities, diagnosis and knowledge of entire nervous system. Existing neuron models have been found to be defective in the aspect of realism. Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism. In this research, a new reconstruction model comprising of the Bounding Cylinder, Curve Interpolation and Gouraud Shading is proposed to visualize neuron model in order to improve realism. The reconstructed model is used to design algorithms for generating neuron branching from neuron SWC data. The Bounding Cylinder and Curve Interpolation methods are used to improve the connected segments of the neuron model using a series of cascaded cylinders along the neuron's connection path. Three control points are proposed between two adjacent neuron segments. Finally, the model is rendered with Gouraud Shading for smoothening of the model surface. This produce a near-perfection model of the natural neurons with attended realism. The model is validated by a group of bioinformatics analysts' responses to a predefined survey. The result shows about 82% acceptance and satisfaction rate.

No MeSH data available.


User's feedback on advantage or strengths obtained from prototype development.(1) Manipulation functions for viewing neuron model from different angles. (2) Different colour presentation for differentiating connected segments of neuron model. (3) Focus on specific neuron data for visualization and comparison i.e. usage of neuron SWC data.
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Figure 14: User's feedback on advantage or strengths obtained from prototype development.(1) Manipulation functions for viewing neuron model from different angles. (2) Different colour presentation for differentiating connected segments of neuron model. (3) Focus on specific neuron data for visualization and comparison i.e. usage of neuron SWC data.

Mentions: However, 100% is recorded about the need that neuron data are necessary to be visualized in three-dimension. The percentages of characteristics by choice in terms of individual consideration for the acceptability are presented in Figure 13. Based on result shown in Figure 13, the highest element to consider for development of neuron visualization is the realistic aspect in neuron model presentation. About 82% of the respondents agreed that the result from this proposed model is able to visualize neuron data in three-dimension more effectively for intuitive data explorations. Most respondents agreed that with this model, coloration of the pigments is very helpful in differentiating connected segment of the neuron model which makes visualization very intuitive. The other strengths are as shown in Figure 14. From the selected users’ feedback, the proposed prototype achieves an average performance and aligns with existing neuron applications’ requirement. This is measured in term of user satisfaction in interacting with developed prototype. The proposed neuron model is similar with the original (biological) neuron and presentation of different colours that was used to differentiate neuron connection types. The overall result of user acceptance and satisfaction towards developed prototype is described in Figure 15. The lower rating starting from 1 indicated as a low performance achievement to the highest performance with rating indicated as 5.


Curve interpolation model for visualising disjointed neural elements.

Rahim MS, Razzali N, Sunar MS, Altameem A, Rehman A - Neural Regen Res (2012)

User's feedback on advantage or strengths obtained from prototype development.(1) Manipulation functions for viewing neuron model from different angles. (2) Different colour presentation for differentiating connected segments of neuron model. (3) Focus on specific neuron data for visualization and comparison i.e. usage of neuron SWC data.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4308766&req=5

Figure 14: User's feedback on advantage or strengths obtained from prototype development.(1) Manipulation functions for viewing neuron model from different angles. (2) Different colour presentation for differentiating connected segments of neuron model. (3) Focus on specific neuron data for visualization and comparison i.e. usage of neuron SWC data.
Mentions: However, 100% is recorded about the need that neuron data are necessary to be visualized in three-dimension. The percentages of characteristics by choice in terms of individual consideration for the acceptability are presented in Figure 13. Based on result shown in Figure 13, the highest element to consider for development of neuron visualization is the realistic aspect in neuron model presentation. About 82% of the respondents agreed that the result from this proposed model is able to visualize neuron data in three-dimension more effectively for intuitive data explorations. Most respondents agreed that with this model, coloration of the pigments is very helpful in differentiating connected segment of the neuron model which makes visualization very intuitive. The other strengths are as shown in Figure 14. From the selected users’ feedback, the proposed prototype achieves an average performance and aligns with existing neuron applications’ requirement. This is measured in term of user satisfaction in interacting with developed prototype. The proposed neuron model is similar with the original (biological) neuron and presentation of different colours that was used to differentiate neuron connection types. The overall result of user acceptance and satisfaction towards developed prototype is described in Figure 15. The lower rating starting from 1 indicated as a low performance achievement to the highest performance with rating indicated as 5.

Bottom Line: Existing neuron models have been found to be defective in the aspect of realism.Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism.The result shows about 82% acceptance and satisfaction rate.

View Article: PubMed Central - PubMed

Affiliation: UTMViCubeLab, Department of Computer Graphics and Multimedia, FSKSM, University of Technology, Skudai 81310, Malaysia.

ABSTRACT
Neuron cell are built from a myriad of axon and dendrite structures. It transmits electrochemical signals between the brain and the nervous system. Three-dimensional visualization of neuron structure could help to facilitate deeper understanding of neuron and its models. An accurate neuron model could aid understanding of brain's functionalities, diagnosis and knowledge of entire nervous system. Existing neuron models have been found to be defective in the aspect of realism. Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism. In this research, a new reconstruction model comprising of the Bounding Cylinder, Curve Interpolation and Gouraud Shading is proposed to visualize neuron model in order to improve realism. The reconstructed model is used to design algorithms for generating neuron branching from neuron SWC data. The Bounding Cylinder and Curve Interpolation methods are used to improve the connected segments of the neuron model using a series of cascaded cylinders along the neuron's connection path. Three control points are proposed between two adjacent neuron segments. Finally, the model is rendered with Gouraud Shading for smoothening of the model surface. This produce a near-perfection model of the natural neurons with attended realism. The model is validated by a group of bioinformatics analysts' responses to a predefined survey. The result shows about 82% acceptance and satisfaction rate.

No MeSH data available.