| Autor: |
Fernández Patón, Matías, Cerdá Alberich, Leonor, Sangüesa Nebot, Cinta, Martínez de las Heras, Blanca, Veiga Canuto, Diana, Cañete Nieto, Adela, Martí-Bonmatí, Luis |
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| Zdroj: |
Journal of Digital Imaging; Oct2021, Vol. 34 Issue 5, p1134-1145, 12p, 1 Color Photograph, 3 Black and White Photographs, 1 Diagram, 3 Charts, 2 Graphs |
| Abstrakt: |
Several noise sources, such as the Johnson–Nyquist noise, affect MR images disturbing the visualization of structures and affecting the subsequent extraction of radiomic data. We evaluate the performance of 5 denoising filters (anisotropic diffusion filter (ADF), curvature flow filter (CFF), Gaussian filter (GF), non-local means filter (NLMF), and unbiased non-local means (UNLMF)), with 33 different settings, in T2-weighted MR images of phantoms (N = 112) and neuroblastoma patients (N = 25). Filters were discarded until the most optimal solutions were obtained according to 3 image quality metrics: peak signal-to-noise ratio (PSNR), edge-strength similarity–based image quality metric (ESSIM), and noise (standard deviation of the signal intensity of a region in the background area). The selected filters were ADFs and UNLMs. From them, 107 radiomics features preservation at 4 progressively added noise levels were studied. The ADF with a conductance of 1 and 2 iterations standardized the radiomic features, improving reproducibility and quality metrics. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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