Flexibility description of the MET protein stalk based on the use of non-uniform B-splines

Authors:
Magnus Gedda;Stina Svensson
Affiliations:
Uppsala University, Swedish University of Agricultural Sciences, Centre for Image Analysis, Uppsala, Sweden;Uppsala University/Swedish University of Agricultural Sciences, Uppsala, Sweden
Venue:
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Year:
2007

Citing 9
Cited 1

A fast sequential method for polygonal approximation of digitized curves

Computer Vision, Graphics, and Image Processing
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations

IEEE Transactions on Pattern Analysis and Machine Intelligence
3d Computer Graphics

3d Computer Graphics
Fuzzy distance transform: theory, algorithms, and applications

Computer Vision and Image Understanding
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Using a fuzzy framework for delineation and decomposition of Immunoglobulin G in cryo electron tomographic images

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Estimation of curvature along curves with application to fibres in 3D images of paper

SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
An objective comparison between gray weighted distance transforms and weighted distance transforms on curved spaces

DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
Automatic ultrastructure segmentation of reconstructed CryoEM maps of icosahedral viruses

IEEE Transactions on Image Processing

Image processing system for localising macromolecules in cryo-electron tomography

Machine Graphics & Vision International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

The MET protein controls growth, invasion, and metastasis in cancer cells and is thereby of interest to study, for example from a structural point of view. For individual particle imaging by Cryo-Electron Tomography of the MET protein, or other proteins, dedicated image analysis methods are required to extract information in a robust way as the images have low contrast and resolution (with respect to the size of the imaged structure). We present a method to identify the two parts of the MET protein, β-propeller and stalk, using a fuzzy framework. Furthermore, we describe how a representation of the MET stalk, denoted stalk curve, can be identified based on the use of non-uniform B-splines. The stalk curve is used to extract relevant geometrical information about the stalk, e.g., to facilitate curvature and length measurements.