Name
Abstract | ||
|---|---|---|
Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, automated analysis of dermoscopy images has become an important research area. Border detection is often the first step in this analysis. In many cases, the lesion can be roughly separated from the background skin using a thresholding method applied to the blue channel. However, no single thresholding method appears to be robust enough to successfully handle a wide variety of dermoscopic images. In this paper, we present an automated method for detecting lesion borders in dermoscopy images using a fusion of several thresholding methods. Experiments on a difficult set of 90 images demonstrate that the proposed method achieves both fast and accurate results when compared to six state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICIP.2010.5653514 | Image Processing |
Keywords | Field | DocType |
diseases,edge detection,image fusion,image segmentation,medical image processing,patient diagnosis,pigments,skin,automated analysis,dermoscopy image,melanoma diagnosis,pigmented skin lesion,robust border detection,threshold fusion | Computer vision,Pattern recognition,Pigmented skin,Image fusion,Imaging modalities,Computer science,Edge detection,Robustness (computer science),Image segmentation,Artificial intelligence,Pixel,Thresholding | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-7993-1 | 978-1-4244-7993-1 | 8 |
PageRank | References | Authors |
0.59 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Emre Celebi | 1 | 1240 | 84.15 |
| Sae Hwang | 2 | 247 | 17.88 |
| Iyatomi, Hitoshi | 3 | 17 | 1.47 |
| Gerald Schaefer | 4 | 430 | 27.50 |