↓ Skip to main content

Implementation and clinical application of a deformation method for fast simulation of biological tissue formed by fibers and fluid

Overview of attention for article published in Source Code for Biology and Medicine, April 2016
Altmetric Badge

Mentioned by

twitter
1 tweeter

Readers on

mendeley
14 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Implementation and clinical application of a deformation method for fast simulation of biological tissue formed by fibers and fluid
Published in
Source Code for Biology and Medicine, April 2016
DOI 10.1186/s13029-016-0054-x
Pubmed ID
Authors

Ana Gabriella de Oliveira Sardinha, Ana Gabriella de Oliveira Sardinha, Ceres Nunes de Resende Oyama, Armando Maroja, Ivan F. Costa

Abstract

The aim of this paper is to provide a general discussion, algorithm, and actual working programs of the deformation method for fast simulation of biological tissue formed by fibers and fluid. In order to demonstrate the benefit of the clinical applications software, we successfully used our computational program to deform a 3D breast image acquired from patients, using a 3D scanner, in a real hospital environment. The method implements a quasi-static solution for elastic global deformations of objects. Each pair of vertices of the surface is connected and defines an elastic fiber. The set of all the elastic fibers defines a mesh of smaller size than the volumetric meshes, allowing for simulation of complex objects with less computational effort. The behavior similar to the stress tensor is obtained by the volume conservation equation that mixes the 3D coordinates. Step by step, we show the computational implementation of this approach. As an example, a 2D rectangle formed by only 4 vertices is solved and, for this simple geometry, all intermediate results are shown. On the other hand, actual implementations of these ideas in the form of working computer routines are provided for general 3D objects, including a clinical application.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 29%
Student > Ph. D. Student 3 21%
Student > Master 3 21%
Student > Doctoral Student 1 7%
Unknown 3 21%
Readers by discipline Count As %
Psychology 3 21%
Computer Science 3 21%
Engineering 2 14%
Earth and Planetary Sciences 1 7%
Social Sciences 1 7%
Other 1 7%
Unknown 3 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 April 2016.
All research outputs
#6,543,358
of 7,554,544 outputs
Outputs from Source Code for Biology and Medicine
#100
of 117 outputs
Outputs of similar age
#226,297
of 268,606 outputs
Outputs of similar age from Source Code for Biology and Medicine
#4
of 4 outputs
Altmetric has tracked 7,554,544 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 117 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 268,606 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.