Paper Info
Title
Microtubule Dynamics Classification Using a Statistical Model of the Movement of Outer Tips
Abstract
A new method is proposed for tracking the dynamics of microtubules. It combines a salient point extraction mechanism for segmenting plus-end tips, a robust tracking method capable of locating the trajectories of a large number of feature points, and a classification algorithm capable of determining if the level of activity of a given microtubule video is typical of that of a treated or a control cell. Our method does not rely on the precise tracking of a single microtubule like many previous works, but instead focuses on the generalized movement of ending tips as a whole, which gives a more statistically reliable interpretation of the movement of microtubules. The proposed algorithm is tested using twenty videos of breast cancer microtubules - ten are treated with Taxol and ten are control. We are able to correctly classify those test videos 85% of the time, which is comparable in accuracy, but uses a less complex algorithm than other algorithms.
Year
DOI
Venue
2007
10.1109/BIBE.2007.4375607
BIBE
Keywords
Field
DocType
biological organs,biomedical optical imaging,cancer,cellular biophysics,gynaecology,image classification,image segmentation,medical image processing,molecular biophysics,proteins,video signal processing,breast cancer,microtubule dynamics classification,plus-end tip segmentation,robust tracking method,salient point extraction,statistical model
Computer vision,Microtubule dynamics,Cellular biophysics,Computer science,Image segmentation,Artificial intelligence,Statistical model,Bioinformatics,Contextual image classification,Salient
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
7
Name
Order
Citations
PageRank
Christopher Alberti1212.79
Jean-philippe Villaréal200.68
Delano Billingsley300.34
Koon Yin Kong482.90
Adam I. Marcus572.49
Paraskevi Giannakakou671.81
May D. Wang735566.20