Three-Dimensional Analysis of Spiny Dendrites Using Straightening and Unrolling Transforms

Morales, Juan; Benavides-Piccione, Ruth; Rodríguez, Antonio; Pastor, Luis; Yuste, Rafael; DeFelipe, Javier

doi:10.1007/s12021-012-9153-2

Cited by 5 publications

(3 citation statements)

References 25 publications

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“…InTool Explorer has proved to be very useful for its intended purpose, providing new insights into the raw data extracted from a variety of analyses performed in different patients and brain areas in AD. The application provides new interactive support (including other tools previously developed by the authors, e.g., Morales et al, 2011 , 2012 ; Brito et al, 2013 ; Toharia et al, 2014 , 2016 ), which improves and facilitates neuroscientists’ research.…”

Section: Discussionmentioning

confidence: 99%

InTool Explorer: An Interactive Exploratory Analysis Tool for Versatile Visualizations of Neuroscientific Data

et al. 2019

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The bottleneck for progress in many research areas within neuroscience has shifted from the data acquisition to the data analysis stages. In the present article, we propose a method named InTool Explorer that we have developed to perform interactive exploratory data analysis, focusing on neuroanatomy as an example of its utility. This tool is freely-available software that has been designed to facilitate the study of complex neuroscience data. InTool Explorer requires no more than an internet connection and a web browser. The main contribution of this tool is to provide a user-designed canvas for data visualization and interaction, to perform specific exploratory tasks according to the user needs. Moreover, InTool Explorer permits visualization of the datasets in a very dynamic and versatile way using a linked-card approach. For this purpose, the tool allows the user to select among different predefined card types. Each card type offers an abstract data representation, a filtering tool or a set of statistical analysis methods. Additionally, InTool Explorer makes it possible linking raw images to the data. These images can be used by InTool Explorer to define new customized filtering cards. Another significant contribution of this tool is that it allows fast visualization of the data, error finding, and re-evaluation to establish new hypotheses or new lines of research. Thus, regarding its practical application in the laboratory, InTool Explorer provides a new opportunity to study and analyze neuroscience data prior to any statistical analysis being carried out.

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Section: Discussionmentioning

confidence: 99%

InTool Explorer: An Interactive Exploratory Analysis Tool for Versatile Visualizations of Neuroscientific Data

et al. 2019

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“…Micro-nutrition is caused either by an excess or deficiency of vitamins and minerals in the diet. Over-nutrition causes obesity and some diet-related non-communicable diseases, sometimes it can also lead to a neurological disorder such as spiny dendrites [1,2]. Just like malnutrition, anemia can be classified into five types aplastic anemia, iron deficiency anemia, sickle cell anemia, thalassemia, and vitamin deficiency anemia.…”

Section: Introductionmentioning

confidence: 99%

Decision-making Support System for Predicting and Eliminating Malnutrition and Anemia

Maasthi,

Gururaj,

Ravi

et al. 2023

TOBIOIJ

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Aims: This study investigates predicting and eliminating malnutrition and anemia using ML Algorithms and comparing all the methods with various malnutrition-based parameters. Background: The health of the nation is more important than the wealth of the nation. Malnutrition and anemia are serious health issues but the least importance is given to eradicate them. Objective: Proper nutrition is an essential component for the survival, growth, and development of infants, children, and women who in turn give birth to infants. Methods: In the proposed system, machine learning approaches are utilized to predict the malnutrition status of children under five years of age and anemia in men and women using old datasets and further providing a suitable diet recommendation to overcome the disease. Classification techniques are being used for malnutrition as well as anemia prediction. Results: Algorithms such as Naïve Bayes classifier (NBC), Decision Tree (DT) algorithm, Random Forest (RF) algorithm, and K-Nearest Neighbor (k-NN) algorithm are utilized for prediction. The results obtained by these algorithms are 94.47%, 85%, 95.49%, and 63.15%. When compared, Naïve Bayes and random forest algorithm provided efficient results for malnutrition and anemia, respectively. Conclusion: By testing and validating, preventive actions can be taken with the help of medical experts and dieticians to reduce malnutrition and anemia conditions among children and elders, respectively.

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“…Specifically, the benefits of incorporating visualization-based approaches into the analysis of complex systems have already become evident in neuroscience research. For example, a method based on the implementation of straightening and unrolling transformations has been recently developed to transform the previously-analyzed 3D structure of spine insertions in dendrites of pyramidal cells to a planar, unfolded arrangement (Morales et al, 2012). The implementation of these visual technologies facilitates the analysis of neuron structure, providing new insights into the organization and distribution patterns of these cells.…”

Section: Introductionmentioning

confidence: 99%

Neuronize: a tool for building realistic neuronal cell morphologies

et al. 2013

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This study presents a tool, Neuronize, for building realistic three-dimensional models of neuronal cells from the morphological information extracted through computer-aided tracing applications. Neuronize consists of a set of methods designed to build 3D neural meshes that approximate the cell membrane at different resolution levels, allowing a balance to be reached between the complexity and the quality of the final model. The main contribution of the present study is the proposal of a novel approach to build a realistic and accurate 3D shape of the soma from the incomplete information stored in the digitally traced neuron, which usually consists of a 2D cell body contour. This technique is based on the deformation of an initial shape driven by the position and thickness of the first order dendrites. The addition of a set of spines along the dendrites completes the model, building a final 3D neuronal cell suitable for its visualization in a wide range of 3D environments.

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Three-Dimensional Analysis of Spiny Dendrites Using Straightening and Unrolling Transforms

Cited by 5 publications

References 25 publications

InTool Explorer: An Interactive Exploratory Analysis Tool for Versatile Visualizations of Neuroscientific Data

InTool Explorer: An Interactive Exploratory Analysis Tool for Versatile Visualizations of Neuroscientific Data

Decision-making Support System for Predicting and Eliminating Malnutrition and Anemia

Neuronize: a tool for building realistic neuronal cell morphologies

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