Computed Tomography Image Reconstruction.
Filtered back projection was used in computed tomography (CT) but produced low-dose CT images that were noisy and included artifacts. Iterative reconstruction was introduced, which reduced noise and demonstrated dose reduction; however, reconstruction times were lengthy and noise texture appeared un...
| Publicado en: | Radiologic Technology Vol. 92; no. 2; pp. 155CT - 172 |
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| Autor principal: | |
| Formato: | CEU diagnostic images exam questions pictorial tables/charts Journal Article |
| Publicado: |
American Society of Radiologic Technologists
Nov/Dec2020
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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=147249117&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 147249117 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00338397 39J jtl: Radiologic Technology issn: 00338397 maglogo: N pubinfo: dt: Nov/Dec2020 vid: 92 iid: 2 pid: 7052 pub: American Society of Radiologic Technologists place: Alburquerque, New Mexico artinfo: ui: 147249117 147249117 147249117 147249117 ppf: 155CT ppct: 17 formats: fmt: @attributes: type: P tig: atl: Computed Tomography Image Reconstruction. aug: au: Seeram, Euclid affil: PhD, FCAMRT, is honorary senior lecturer, University of Sydney sug: subj: Algorithms Utilization Image Processing, Computer Assisted Evaluation Image Processing, Computer Assisted Methods Artificial Intelligence Ethical Issues Tomography, X-Ray Computed Deep Learning Radiology Service Education, Continuing (Credit) Neural Networks (Computer) Electronic Health Records Natural Language Processing Expert Systems ab: Filtered back projection was used in computed tomography (CT) but produced low-dose CT images that were noisy and included artifacts. Iterative reconstruction was introduced, which reduced noise and demonstrated dose reduction; however, reconstruction times were lengthy and noise texture appeared unnatural. Now, artificial intelligence (AI), is being applied to CT image reconstruction. These algorithms are fast and produce images comparable to those produced by iterative reconstruction. This article outlines image reconstruction techniques, including a generalized framework for deep learning. Ethics of AI in radiology also is discussed. pubtype: Academic Journal doctype: CEU diagnostic images exam questions pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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