Literature DB >> 9853375

Towards automatic cell identification in DIC microscopy.

D Young1, C A Glasbey, A J Gray, N J Martin.   

Abstract

A general method is proposed for constructing templates of cells in differential interference contrast (DIC) microscopy. This takes account of the optics which generate DIC images, and is applicable to both transparent and semi-transparent cells of simple and complex shapes. Then, a template matching methodology is presented, which uses fast Fourier transforms to fit templates of a range of sizes and orientations to images. For illustration, this is used to automatically identify and measure individual Candida yeast cells in clusters.

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Year:  1998        PMID： 9853375     DOI： 10.1046/j.1365-2818.1998.00397.x

Source DB:  PubMed          Journal:  J Microsc        ISSN： 0022-2720            Impact factor:   1.758


  5 in total

1.  Force-velocity curves of motor proteins cooperating in vivo.

Authors:  Yuri Shtridelman; Thomas Cahyuti; Brigitte Townsend; David DeWitt; Jed C Macosko
Journal:  Cell Biochem Biophys       Date:  2008       Impact factor: 2.194

2.  Adaptive behavior of bacterial mechanosensitive channels is coupled to membrane mechanics.

Authors:  Vladislav Belyy; Kishore Kamaraju; Bradley Akitake; Andriy Anishkin; Sergei Sukharev
Journal:  J Gen Physiol       Date:  2010-06       Impact factor: 4.086

3.  Significantly improved precision of cell migration analysis in time-lapse video microscopy through use of a fully automated tracking system.

Authors:  Johannes Huth; Malte Buchholz; Johann M Kraus; Martin Schmucker; Götz von Wichert; Denis Krndija; Thomas Seufferlein; Thomas M Gress; Hans A Kestler
Journal:  BMC Cell Biol       Date:  2010-04-08       Impact factor: 4.241

4.  Bacterial cell identification in differential interference contrast microscopy images.

Authors:  Boguslaw Obara; Mark A J Roberts; Judith P Armitage; Vicente Grau
Journal:  BMC Bioinformatics       Date:  2013-04-23       Impact factor: 3.169

5.  Multicell migration tracking within angiogenic networks by deep learning-based segmentation and augmented Bayesian filtering.

Authors:  Mengmeng Wang; Lee-Ling Sharon Ong; Justin Dauwels; H Harry Asada
Journal:  J Med Imaging (Bellingham)       Date:  2018-06-13
  5 in total

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