| Paper: | WP-P2.10 |
| Session: | Biomedical Imaging V: Molecular & Cellular Bioimaging / Segmentation |
| Time: | Wednesday, September 19, 14:30 - 17:10 |
| Presentation: |
Poster
|
| Title: |
AUTOMATIC SEGMENTATION OF SKIN LESION IMAGES USING EVOLUTIONARY STRATEGY |
| Authors: |
Ning Situ; University of Houston | | |
| | Xiaojing Yuan; University of Houston | | |
| | George Zouridakis; University of Houston | | |
| | Nizar Mullani; Translite LLC | | |
| Abstract: |
Malignant melanoma has a good prognosis if treated early. Accurate skin lesion segmentation from the background skin is important not only because the shape feature can be directly derived from the process, but also because it can provide a scope for texture analysis. In this paper, we proposed an evolutionary strategy based segmentation algorithm to identify the lesion area by an ellipse. It can detect the lesion automatically without setting parameters manually. The method is validated by experiments and comparisons with manually segmentation by an expert and algorithms developed in [1, 2]. |
