2014
DOI: 10.1098/rsif.2014.0685
|View full text |Cite
|
Sign up to set email alerts
|

Simple and accurate methods for quantifying deformation, disruption, and development in biological tissues

Abstract: When mechanical factors underlie growth, development, disease or healing, they often function through local regions of tissue where deformation is highly concentrated. Current optical techniques to estimate deformation can lack precision and accuracy in such regions due to challenges in distinguishing a region of concentrated deformation from an error in displacement tracking. Here, we present a simple and general technique for improving the accuracy and precision of strain estimation and an associated techniq… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
41
0

Year Published

2015
2015
2023
2023

Publication Types

Select...
6
1

Relationship

4
3

Authors

Journals

citations
Cited by 36 publications
(42 citation statements)
references
References 29 publications
0
41
0
Order By: Relevance
“…The method shows that surface motion can be tracked by utilizing inherent structural properties of the tissue. This approach could be combined with methods such as those of Boyle et al 6 or Witzenburg et al 38 to identify damaged or remodeled regions in a tissue.…”
Section: Discussionmentioning
confidence: 99%
“…The method shows that surface motion can be tracked by utilizing inherent structural properties of the tissue. This approach could be combined with methods such as those of Boyle et al 6 or Witzenburg et al 38 to identify damaged or remodeled regions in a tissue.…”
Section: Discussionmentioning
confidence: 99%
“…Five locations along the length of each specimen were chosen based on identification of distinct features that were tracked using an image registration algorithm. For each successive frame, the regions were tracked using a Newton-Raphson-like method that computes pixel displacements [23]. The manifold was broken into individual segments bounded by a tracked region on either side for 1-dimensional strain calculations.…”
Section: Methodsmentioning
confidence: 99%
“…Strain was calculated using a combination of optical and machine outputs. A strain-tracking algorithm was used to determine strain on video captured during testing [30]. The dimensions of the sample were determined from calibrated points on the fixtures.…”
Section: Methodsmentioning
confidence: 99%