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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 (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.