Silva-2010g
From IEETA
Article
| Title | Image Denoising Methods for Tumor Discrimination in High-Resolution Computed Tomography |
|---|---|
| Author | José Silvestre Silva, Augusto Silva, Beatriz Sousa Santos |
| Journal | Journal of Digital Imaging |
| Volume | 24 |
| Number | 3 |
| Pages | 464-469 |
| Month | June |
| Year | 2011 |
| DOI | 10.1007/s10278-010-9305-6 |
| Group | |
| Group (before 2015) | Signal Processing Laboratory |
| Indexed by ISI | Yes |
Pixel accuracy in images from high-resolution computed tomography (HRCT) is ultimately limited by reconstruction error and noise. While for visual analysis this may not be relevant, for computer-aided quantitative analysis in either densitometric, or shape studies aiming at accurate results, the impact of pixel uncertainty must be taken into consideration. In this work, we study several denoising methods: geometric mean filter, Wiener filtering, and wavelet denoising. The performance of each method was assessed through visual inspection, profile region intensity analysis, and global figures of merit, using images from brain and thoracic phantoms, as well as several real thoracic HRCT images.