Automated nuclei detection in fluorescence microscopy by HEDAR.

Automated Nuclei Detection

Automated nuclei detection in fluorescence microscopy by HEDAR.

Automated Nuclei Detection

At Durham University, my PhD research focussed on the use of mathematical morphology to quantify biological and medical images. One such challenge was the automated detection of ellipse-like objects, such as cell nulcei, in fluorescence microscopy. Working with Philip Jackson and Boguslaw Obara, I developed a new approach to identifying ellipses based on Hilbert-edge detection and ranging (HEDAR) and assumptions based on the shape on an ellipse.

My contribution to this work was funded by EPSRC.

A publication is currently under preparation.

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Chas Nelson
LKAS Research Fellow in Data Science

An interdisciplinary scientist with a background in quantitative microscopy and bioimage analysis.

Publications

Accurate and reliable nuclei identification is an essential part of quantification in microscopy. A range of mathematical and machine …

We present a segmentation software package primarily targeting medical and biological applications, with a high level of visual …

Mathematical morphology is an established field of image processing first introduced as an application of set and lattice theories. …

This article outlines a procedure for speeding up segmentation of images using active mesh systems. Active meshes and other deformable …

Talks

This article outlines a procedure for speeding up segmentation of images using active mesh systems. Active meshes and other deformable …

Often bioimage informatics solutions are developed on a case-by-case system and, once complete, little research goes in to developing …