An evaluation of semiautomatic approaches to contour segmentation applied to fungal hyphae.
Semiautomatic image analysis techniques are particularly useful in biological applications, which commonly generate very complex images, and offer considerable flexibility. However, systematic study of such methods is lacking; most research develops fully automatic algorithms. This paper describes a study to evaluate several different semiautomatic or computer-assisted approaches to contour segmentation within the context of segmenting degraded images of fungal hyphae. Four different types of contour segmentation method, with varying degrees and types of user input, are outlined and applied to hyphal images. The methods are evaluated both quantitatively and qualitatively by comparing results obtained by several test subjects segmenting simulated images qualitatively similar to the hyphal images of interest. An active contour model approach, using control points, emerges as the method to be preferred to three more traditional approaches. Feedback from the image provider indicates that any of the methods described have something useful to offer for segmentation of hyphae.
Department of Statistics and Modelling Science, University of Strathclyde, Glasgow, Scotland, UK.
L M
LM
Inglis
A J
AJ
Gray
D000465:Algorithms; D001699:Biometry; D005658:Fungi / Q000254:growth & development*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*