Name
Abstract | ||
|---|---|---|
When an X-ray image is taken, interactions between tissues of the patient and X-rays cause scattered radiation. The detection of the scattered radiation causes degradation of the image quality. Very common technique for reducing scatter is the antiscatter grid. The grid is effective, but it can not remove all scattering. Another drawback of the grid is that the dose level must be increased, because of the attenuation caused by the grid. Larger the dose level is, larger the health risk became for the patient. Imaging device could be simplified and the dose level decreased if effects of the scattering could be reduced using computational image processing methods. This paper addresses the problem of the scatter compensation from the digital X-ray images. Our algorithm is based on maximum likelihood expectation maximization (MLEM) algorithm derived in [1]. Modified version of this algorithm is presented in this paper. MLEM algorithm increases noise. Because of this SUSAN filter [13] was used after MLEM. Our algorithm reduced scatter to 21% from its original value in the skull image. Also contrast and signal to noise ratio (SNR) were improved. |
Year | Venue | Keywords |
|---|---|---|
2000 | EUSIPCO | estimation,filtering,signal to noise ratio,thorax |
Field | DocType | ISBN |
Computer vision,Median filter,Computer science,Signal-to-noise ratio,Image processing,Image quality,Filter (signal processing),Artificial intelligence,Attenuation,Grid,Digital radiography | Conference | 978-952-1504-43-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Onnia, Vesa | 1 | 24 | 1.99 |
| vesa varjonen | 2 | 0 | 0.34 |
| mari lehtimaki | 3 | 0 | 0.68 |
| M Lehtokangas | 4 | 158 | 21.87 |
| Jukka Saarinen | 5 | 264 | 46.21 |