Name
Title | ||
|---|---|---|
Image Denoising Methods for Tumor Discrimination in High-Resolution Computed Tomography. |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s10278-010-9305-6 | J. Digital Imaging |
Keywords | Field | DocType |
tomographic reconstruction,visual analysis,visual inspection,quantitative analysis,geometric mean,poisson noise,figure of merit,computed tomography,wiener filter | Noise reduction,Wiener filter,Computer vision,Tomographic reconstruction,Visual inspection,Non-local means,Computer science,Pixel,Artificial intelligence,High-resolution computed tomography,Shot noise | Journal |
Volume | Issue | ISSN |
24 | 3 | 1618-727X |
Citations | PageRank | References |
4 | 0.55 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Silvestre Silva | 1 | 29 | 3.96 |
| Augusto Silva | 2 | 45 | 6.53 |
| Beatriz Sousa Santos | 3 | 374 | 45.01 |