Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks.
The aim of this study is to use a multilayer perceptron (MLP) artificial neural network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two-dimensional (2D) microwave tomographic...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 58; no. 2; pp. 433 - 443 |
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| Autores principales: | , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Feb2020
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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=141513929&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141513929 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Feb2020 vid: 58 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 141513929 141513929 NLM31863248 141513929 10.1007/s11517-019-02090-y NLM31863248 141513929 ppf: 433 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks. aug: au: Fajardo, J. E. Lotto, F. P. Vericat, F. Carlevaro, C. M. Irastorza, R. M. affil: Instituto de Física de Líquidos y Sistemas Biológicos CONICET - CCT La Plata, La Plata, Argentina sug: subj: Tomography, X-Ray Computed Methods Calcaneus Heel Physiology Image Processing, Computer Assisted Calcaneus Physiology Heel Electrophysiology Funding Source Human ab: The aim of this study is to use a multilayer perceptron (MLP) artificial neural network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two-dimensional (2D) microwave tomographic array. Computer simulations were performed over 2D dielectric maps inspired by computed tomography (CT) images of human heels for training and testing the MLP. A morphometric analysis was performed to account for the scatterer shape influence on the results. A robustness analysis was also conducted in order to study the MLP performance in noisy conditions. The standard deviations of the relative percentage errors on estimating the dielectric properties of the calcaneus bone were relatively high. Regarding the calcaneus surrounding tissue, the dielectric parameters estimations are better, with relative percentage error standard deviations up to ≈ 15%. The location and size of the calcaneus are always properly estimated with absolute error standard deviations up to ≈ 3 mm. Microwave tomography of the calcaneus using phaseless data. Simulations were inspired in Computed Tomography images from real heels (above). Inverse problem was solved using Multilayer Perceptron Artificial Neural Network (below). pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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