MR Denoising Increases Radiomic Biomarker Precision and Reproducibility in Oncologic Imaging.
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), Gaussia...
| Publicado en: | Journal of Digital Imaging Vol. 34; no. 5; pp. 1134 - 1146 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=153241281&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 153241281 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Oct2021 vid: 34 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 153241281 152363164 153241281 153241281 10.1007/s10278-021-00512-8 153241281 ppf: 1134 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: MR Denoising Increases Radiomic Biomarker Precision and Reproducibility in Oncologic Imaging. aug: au: Fernández Patón, Matías Cerdá Alberich, Leonor Sangüesa Nebot, Cinta Martínez de las Heras, Blanca Veiga Canuto, Diana Cañete Nieto, Adela Martí-Bonmatí, Luis affil: Grupo de Investigación Biomédica en Imagen, Instituto de Investigación Sanitaria La Fe, Avenida Fernando Abril Martorell, 106 Torre A 7planta, 46026, Valencia, Spain sug: subj: Magnetic Resonance Imaging Methods Tumor Markers, Biological Precision Reproducibility of Results Oncologic Care Diagnostic Imaging Human Image Processing, Computer Assisted Noise Adverse Effects Product Evaluation Phantoms, Imaging Neuroblastoma Cancer Patients ab: 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. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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