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.
|Publication status||E-pub ahead of print - 9 Jan 2009|
|Event||IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications - Sousse, Tunisia|
Duration: 24 Nov 2008 → 26 Nov 2008
|Conference||IPTA 2008: International Workshops on Image Processing Theory, Tools and Applications|
|Period||24/11/08 → 26/11/08|
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