Analysis and recognition of touching cell images based on morphological structures

Authors:
Donggang Yu;Tuan D. Pham;Xiaobo Zhou
Affiliations:
School of Design, Communication and Information Technology, The University of Newcastle, Callaghan, NSW 2308, Australia;School of Information Technology and Electrical Engineering, ADFA, The University of New South Wales, Canberra, ACT 2600, Australia;HCNR Centre for Bioinformatics, Harvard Medical School, Boston, MA 02215, USA
Venue:
Computers in Biology and Medicine
Year:
2009

Citing 7
Cited 1

Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves

IEEE Transactions on Pattern Analysis and Machine Intelligence
A buyer's guide to conic fitting

BMVC '95 Proceedings of the 6th British conference on Machine vision (Vol. 2)
Direct Least Square Fitting of Ellipses

IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing

Digital Image Processing
Image Processing, Analysis, and Machine Vision

Image Processing, Analysis, and Machine Vision
An Efficient Algorithm for Smoothing Binary Image Contours

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2

Guaranteed ellipse fitting with the sampson distance

ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automated analysis and recognition of cell-nuclear phases using fluorescence microscopy images play an important role for high-content screening. A major task of automated imaging based high-content screening is to segment and reconstruct each cell from the touching cell images. In this paper we present new useful method for recognizing morphological structural models of touching cells, detecting segmentation points, determining the number of segmented cells in touching cell image, finding the related data of segmented cell arcs and reconstructing segmented cells. The conceptual frameworks are based on the morphological structures where a series of structural points and their morphological relationships are established. Experiment results have shown the efficient application of the new method for analysis and recognition of touching cell images of high-content screening.