Name
Title | ||
|---|---|---|
Automated Diagnosis of Skin Cancer: Using Digital Image Processing and Mixture-of-Experts |
Abstract | ||
|---|---|---|
Abstract: The incidence of malignant melanoma, the most lethal formof skin cancers, has risen rapidly during the last decades. Fortunately,if detected early, even malignant melanoma can be treated successfully.Thus, in recent years, methods for automated detection and diagnosis ofskin cancer, particulary malignant melanoma, have elicited much interest.In this paper we present an articial neural network approach forthe classication of skin lesions. Sophisticated image processing, feature... |
Year | Venue | Keywords |
|---|---|---|
2001 | Bildverarbeitung für die Medizin | digital image processing |
Field | DocType | Citations |
Biomedical engineering,Image processing,Mixture of experts,Artificial intelligence,Artificial neural network,Computer vision,Pattern recognition,Skin lesion,Skin cancer,Feature extraction,Melanoma,Engineering,Digital image processing | Conference | 4 |
PageRank | References | Authors |
0.94 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Kreutz | 1 | 5 | 1.63 |
| Maik Anschütz | 2 | 4 | 1.27 |
| Thorsten Grünendick | 3 | 8 | 2.55 |
| Thorsten Grünendick | 4 | 8 | 2.55 |
| Stefan Gehlen | 5 | 84 | 6.18 |
| klaus peter hoffmann | 6 | 4 | 0.94 |