Group average difference: a termination criterion for active contour
Related Experiment Video
Updated: May 30, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Tong Kuan Chuah1, Jun Hong Lim, Chueh Loo Poh
1Division of Bioengineering, School of Chemical & Biomedical Engineering, Nanyang Technological University, N1.3-B2-09, 70 Nanyang Drive, Singapore, 637457, Singapore.
Abstract:
This paper presents a termination criterion for active contour that does not involve alteration of the energy functional. The criterion is based on the area difference of the contour during evolution. In this criterion, the evolution of the contour terminates when the area difference fluctuates around a constant. The termination criterion is tested using parametric gradient vector flow active contour with contour resampling and normal force selection. The usefulness of the criterion is shown through its trend, speed, accuracy, shape insensitivity, and insensitivity to contour resampling. The metric used in the proposed criterion demonstrated a steadily decreasing trend. For automatic implementation in which different shapes need to be segmented, the proposed criterion demonstrated almost 50% and 60% total time reduction while achieving similar accuracy as compared with the pixel movement-based method in the segmentation of synthetic and real medical images, respectively. Our results also show that the proposed termination criterion is insensitive to shape variation and contour resampling. The criterion also possesses potential to be used for other kinds of snakes.
More Related Videos
Related Concept Videos
Area Between Curves: Problem Solving
Difference from Background: Limit of Detection
The LOD indicates the presence or absence...
Normal and Tangetial Components: Problem Solving
Mean Absolute Deviation
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
Quantifying and Rejecting Outliers: The Grubbs Test
Trimmed Mean
Although certain measures of central tendency are not sensitive to outliers, there are alternative versions of the mean that get around the...

