Name
Abstract | ||
|---|---|---|
•A novel medical image enhancement method based on Genetic Algorithms is proposed.•MedGA enhances images characterized by nearly bimodal gray level histograms.•The fitness function strengthens the two underlying intensity distributions.•MedGA considerably outperforms the classical image enhancement techniques.•MedGA achieves excellent results in terms of signal and perceived image quality. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2018.11.013 | Expert Systems with Applications |
Keywords | Field | DocType |
Medical imaging systems,Image enhancement,Genetic Algorithms,Magnetic resonance imaging,Bimodal image histogram,Uterine fibroids | Data mining,Histogram,Computer vision,Equalization (audio),Medical imaging,Computer science,Image processing,Image quality,Artificial intelligence,Histogram equalization,Genetic algorithm,Encoding (memory) | Journal |
Volume | ISSN | Citations |
119 | 0957-4174 | 6 |
PageRank | References | Authors |
0.47 | 29 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonardo Rundo | 1 | 25 | 6.40 |
| Andrea Tangherloni | 2 | 40 | 7.88 |
| Marco S. Nobile | 3 | 143 | 23.69 |
| Carmelo Militello | 4 | 112 | 11.68 |
| Daniela Besozzi | 5 | 391 | 39.10 |
| Giancarlo Mauri | 6 | 2106 | 297.38 |
| Paolo Cazzaniga | 7 | 235 | 27.16 |