UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Segmentation of phase contrast microscopy images based on multi-scale local Basic Image Features histograms

Jaccard, N; Szita, N; Griffin, LD; (2017) Segmentation of phase contrast microscopy images based on multi-scale local Basic Image Features histograms. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization , 5 (5) pp. 359-367. 10.1080/21681163.2015.1016243. Green open access

[img]
Preview
Text
Segmentation of phase contrast microscopy images based on multi scale local Basic Image Features histograms.pdf - Published version

Download (1MB) | Preview

Abstract

Phase contrast microscopy (PCM) is routinely used for the inspection of adherent cell cultures in all fields of biology and biomedicine. Key decisions for experimental protocols are often taken by an operator based on typically qualitative observations. However, automated processing and analysis of PCM images remain challenging due to the low contrast between foreground objects (cells) and background as well as various imaging artefacts. We propose a trainable pixel-wise segmentation approach whereby image structures and symmetries are encoded in the form of multi-scale Basic Image Features local histograms, and classification of them is learned by random decision trees. This approach was validated for segmentation of cell versus background, and discrimination between two different cell types. Performance close to that of state-of-the-art specialised algorithms was achieved despite the general nature of the method. The low processing time ( < 4 s per 1280 × 960 pixel images) is suitable for batch processing of experimental data as well as for interactive segmentation applications.

Type: Article
Title: Segmentation of phase contrast microscopy images based on multi-scale local Basic Image Features histograms
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/21681163.2015.1016243
Publisher version: http://dx.doi.org/10.1080/21681163.2015.1016243
Language: English
Additional information: Copyright © 2015 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Segmentation, phase contrast microscopy, trainable segmentation, Basic Image Features, local feature histograms, random forest
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1502127
Downloads since deposit
132Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item