Content area

Abstract

Elongated structures are widely found in biological systems such as cell cytoskeleton and neurons dendritic tree. These structures are observed through optical microscopy and quantified by image processing techniques. However, in fine structures such as filaments quantification methods commonly fail to identify them due to their small size, irregular intensity, and intersections. In this work we propose an image processing method to identify filaments by introducing novel geometrical constraints based on maximal filaments distance and curvature in order to improve segmentation. An example application is shown by applying the proposed method to stress fibers of culture cells. Our work also illustrates how fiber identification can be formulated as an optimization problem.

Details

Title
Geometrical constraints to improve elongated structures segmentation applied to actin filaments
Publication title
Source details
6th Chilean Conference on Pattern Recognition (CCPR)
Publication year
2014
Publication date
Nov 10, 2014
Publisher
The Institution of Engineering & Technology
Place of publication
Stevenage
Country of publication
United Kingdom
Publication subject
ISBN
978-1-78561-081-3
Source type
Conference Paper
Language of publication
English
Document type
Journal Article
ProQuest document ID
1776477231
Document URL
https://www.proquest.com/conference-papers-proceedings/geometrical-constraints-improve-elongated/docview/1776477231/se-2?accountid=208611
Copyright
Copyright The Institution of Engineering & Technology Nov 10, 2014
Last updated
2024-08-27
Database
ProQuest One Academic