Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis

Huaizhong Zhang, Philip Morrow, Sally McClean, Kurt Saetzler

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

In this paper we discuss how the classical geodesic active contours (GAC) model is enhanced by incorporating ‘prior’ information into the scheme. The modified model is applied to biomedical imagery, specifically serial ultrathin electron microscopy sections. The approach used is to apply prior analysis on a training set of data and provide geometric information about the target object during the process of curve evolution. The experimental results and analysis for both synthetic and real images show that the approach performs better than our previous method. It can be implemented semi-automated fashion giving significant improvements compared to a manual approach.
Original languageEnglish
Pages1-7
DOIs
Publication statusE-pub ahead of print - 9 Jan 2009
EventIPTA 2008: International Workshops on Image Processing Theory, Tools and Applications - Sousse, Tunisia
Duration: 24 Nov 200826 Nov 2008

Conference

ConferenceIPTA 2008: International Workshops on Image Processing Theory, Tools and Applications
CountryTunisia
CitySousse
Period24/11/0826/11/08

Fingerprint

Microscopic examination

Cite this

Zhang, H., Morrow, P., McClean, S., & Saetzler, K. (2009). Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis. 1-7. Paper presented at IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications, Sousse, Tunisia. https://doi.org/10.1109/IPTA.2008.4743746
Zhang, Huaizhong ; Morrow, Philip ; McClean, Sally ; Saetzler, Kurt. / Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis. Paper presented at IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications, Sousse, Tunisia.
@conference{020e60b5358648c188c724a3c3bd34f8,
title = "Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis",
abstract = "In this paper we discuss how the classical geodesic active contours (GAC) model is enhanced by incorporating ‘prior’ information into the scheme. The modified model is applied to biomedical imagery, specifically serial ultrathin electron microscopy sections. The approach used is to apply prior analysis on a training set of data and provide geometric information about the target object during the process of curve evolution. The experimental results and analysis for both synthetic and real images show that the approach performs better than our previous method. It can be implemented semi-automated fashion giving significant improvements compared to a manual approach.",
author = "Huaizhong Zhang and Philip Morrow and Sally McClean and Kurt Saetzler",
year = "2009",
month = "1",
day = "9",
doi = "10.1109/IPTA.2008.4743746",
language = "English",
pages = "1--7",
note = "IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications ; Conference date: 24-11-2008 Through 26-11-2008",

}

Zhang, H, Morrow, P, McClean, S & Saetzler, K 2009, 'Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis' Paper presented at IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications, Sousse, Tunisia, 24/11/08 - 26/11/08, pp. 1-7. https://doi.org/10.1109/IPTA.2008.4743746

Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis. / Zhang, Huaizhong; Morrow, Philip; McClean, Sally; Saetzler, Kurt.

2009. 1-7 Paper presented at IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications, Sousse, Tunisia.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis

AU - Zhang, Huaizhong

AU - Morrow, Philip

AU - McClean, Sally

AU - Saetzler, Kurt

PY - 2009/1/9

Y1 - 2009/1/9

N2 - In this paper we discuss how the classical geodesic active contours (GAC) model is enhanced by incorporating ‘prior’ information into the scheme. The modified model is applied to biomedical imagery, specifically serial ultrathin electron microscopy sections. The approach used is to apply prior analysis on a training set of data and provide geometric information about the target object during the process of curve evolution. The experimental results and analysis for both synthetic and real images show that the approach performs better than our previous method. It can be implemented semi-automated fashion giving significant improvements compared to a manual approach.

AB - In this paper we discuss how the classical geodesic active contours (GAC) model is enhanced by incorporating ‘prior’ information into the scheme. The modified model is applied to biomedical imagery, specifically serial ultrathin electron microscopy sections. The approach used is to apply prior analysis on a training set of data and provide geometric information about the target object during the process of curve evolution. The experimental results and analysis for both synthetic and real images show that the approach performs better than our previous method. It can be implemented semi-automated fashion giving significant improvements compared to a manual approach.

U2 - 10.1109/IPTA.2008.4743746

DO - 10.1109/IPTA.2008.4743746

M3 - Paper

SP - 1

EP - 7

ER -

Zhang H, Morrow P, McClean S, Saetzler K. Contour Detection of Labelled Cellular Structures from Serial Ultrathin Electron Microscopy Sections using GAC and Prior Analysis. 2009. Paper presented at IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications, Sousse, Tunisia. https://doi.org/10.1109/IPTA.2008.4743746