Tip-Seeking Active Contours for Bioimage Segmentation

In the present paper, we address the problem of segmenting biological objects featuring corners. The main ingredients of our approach are automated feature-detection methods and mechanisms for introducing kinks in parametric spline snakes. We formulate a novel corner potential that enables the accurate segmentation of objects exhibiting sharp tips or acute angles. The optimization of active contours using the proposed keypoint-based energy yields robuster segmentation results and requires fewer parameters than traditional spline-snake approaches for the same task. The performance of our method is illustrated on microscopic images of two families of Rhabditidse roundworms.


Published in:
Proceedings of the Twelfth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'15), Brooklyn NY, USA, 544–547
Year:
2015
Publisher:
IEEE
Laboratories:




 Record created 2015-09-18, last modified 2018-03-17

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