Name
Title | ||
|---|---|---|
Exploring the color feature power for psoriasis risk stratification and classification: A data mining paradigm. |
Abstract | ||
|---|---|---|
A large percentage of dermatologist׳s decision in psoriasis disease assessment is based on color. The current computer-aided diagnosis systems for psoriasis risk stratification and classification lack the vigor of color paradigm. The paper presents an automated psoriasis computer-aided diagnosis (pCAD) system for classification of psoriasis skin images into psoriatic lesion and healthy skin, which solves the two major challenges: (i) fulfills the color feature requirements and (ii) selects the powerful dominant color features while retaining high classification accuracy. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.compbiomed.2015.07.021 | Computers in Biology and Medicine |
Keywords | Field | DocType |
Psoriasis,Color space,PCA,Classification,Feature power,Reliability | Computer vision,Color space,R-factor (crystallography),Pattern recognition,Feature selection,Computer science,Support vector machine,Feature extraction,Polynomial kernel,Artificial intelligence,Principal component analysis,Grayscale | Journal |
Volume | ISSN | Citations |
65 | 0010-4825 | 8 |
PageRank | References | Authors |
0.51 | 19 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vimal K. Shrivastava | 1 | 61 | 6.71 |
| Narendra D. Londhe | 2 | 98 | 13.85 |
| Rajendra S. Sonawane | 3 | 52 | 4.66 |
| Jasjit S. Suri | 4 | 1754 | 128.89 |