A semi-automated system based on level sets and invariant spatial interrelation shape features for Caenorhabditis elegans phenotypes

作者：Abdelsamea Mohammed M^*

来源：Journal of Visual Communication and Image Representation, 2016, 41: 314-323.

DOI：10.1016/j.jvcir.2016.10.011

• Level sets
• Sign pressure force
• Axis of least inertia
• Image-based feature classification
• Shape-based invariant feature
• C. elegans phenotypes

Caenorhabditis elegans shares several molecular and physiological homologies with humans and thus plays a key role in studying biological processes. As a consequence, much progress has been made in automating the analysis of C. elegans. However, there is still a strong need to achieve more progress in automating the analysis of static images of adult worms. In this paper, a three-phase semi-automated system has been proposed. As a first phase, a novel segmentation framework, based on variational level sets and local pressure force function, has been introduced to handle effectively images corrupted with intensity inhomogeneity. Then, a set of robust invariant symbolic features for high-throughput screening of image-based C elegans phenotypes are extracted. Finally, a classification model is applied to discriminate between the different subsets. The proposed system demonstrates its effectiveness in measuring morphological phenotypes in individual worms of C elegans.

• 出版日期2016-11