From images to clinical insights: an educational review on radiomics in lung diseases.
Radiological imaging is a cornerstone in the clinical workup of lung diseases. Radiomics represents a significant advancement in clinical lung imaging, offering a powerful tool to complement traditional qualitative image analysis. Radiomic features are quantitative and computationally describe shape...
| Publicado en: | Breathe Vol. 21; no. 1; pp. 1 - 15 |
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| Autores principales: | , , , |
| Formato: | diagnostic images pictorial review tables/charts Journal Article |
| Publicado: |
European Respiratory Society
Jan2025
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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=183843876&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 183843876 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 18106838 85SQ jtl: Breathe issn: 18106838 maglogo: N pubinfo: dt: Jan2025 vid: 21 iid: 1 pid: 76609 pub: European Respiratory Society artinfo: ui: 183843876 183843876 183843876 10.1183/20734735.0225-2023 183843876 ppf: 1 ppct: 14 formats: fmt: @attributes: type: P tig: atl: From images to clinical insights: an educational review on radiomics in lung diseases. aug: au: Magnin, Cheryl Y. Lauer, David Ammeter, Michael Gote-Schniering, Janine affil: Department of Rheumatology and Immunology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland sug: subj: Lung Diseases Diagnosis Radiomics Lung Diseases Prognosis Pulmonary Medicine Treatment Outcomes Workflow Decision Making, Clinical Lung Diseases Physiopathology Machine Learning Imaging, Three-Dimensional Technology, Medical ab: Radiological imaging is a cornerstone in the clinical workup of lung diseases. Radiomics represents a significant advancement in clinical lung imaging, offering a powerful tool to complement traditional qualitative image analysis. Radiomic features are quantitative and computationally describe shape, intensity, texture and wavelet characteristics from medical images that can uncover detailed and often subtle information that goes beyond the visual capabilities of radiological examiners. By extracting this quantitative information, radiomics can provide deep insights into the pathophysiology of lung diseases and support clinical decision-making as well as personalised medicine approaches. In this educational review, we provide a step-by-step guide to radiomics-based medical image analysis, discussing the technical challenges and pitfalls, and outline the potential clinical applications of radiomics in diagnosing, prognosticating and evaluating treatment responses in respiratory medicine. pubtype: Academic Journal doctype: diagnostic images pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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