Massey, Elizabeth and Lowell, James and Hunter, Andrew and Steele, David (2009) Lesion boundary segmentation using level set methods. In: VisApp - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1, February 5-8, 2009, Lisbon, Portugal.
|Item Type:||Conference or Workshop Item (Paper)|
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|Divisions:||College of Science > School of Computer Science|
|Abstract:||This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object. We implement the level set using a fast upwind scheme and compare the proposed method against five other segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician marked-up boundaries as ground truth.|
|Date Deposited:||15 Oct 2008 18:00|
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