A superpixel based post-processing approach for segmenting dermoscopy images
Advanced Computational Intelligence(2013)
Abstract
Malignant melanoma is among the most rapidly increasing cancers in the world. Image border detection is often the first step to characterize skin lesion for the follow-up computer-aided diagnosis. As the existing segmentation techniques tend to find the sharpest pigment change in the dermoscopy images, the detected lesion borders are mostly contained inside the borders delineated manually by the dermatologists. Therefore, post-processing steps are needed to smooth and expand the segmented borders. In this paper, we propose a novel post-processing approach to enhance the accuracy of segmentation results, by merging superpixels which intersect with skin lesion area based on skin color consistency. The experimental results on the real dermoscopy image set show that the proposed method can improve the overall performance in terms of both accuracy and robustness.
MoreTranslated text
Key words
superpixel,image border detection,malignant melanoma,lesion border detection,melanoma,skin lesion characteristics,superpixel based post-processing approach,biomedical transducers,image segmentation,skin color consistency,dermoscopy image segmentation,dermatologist,image sensors,cancer,post-processing,dermoscopy image,skin,computer-aided diagnosis,medical image processing,image colour analysis
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined