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A role for artificial intelligence in molecular imaging of infection and inflammation.
Schwenck, Johannes; Kneilling, Manfred; Riksen, Niels P; la Fougère, Christian; Mulder, Douwe J; Slart, Riemer J H A; Aarntzen, Erik H J G.
Affiliation
  • Schwenck J; Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University, Tübingen, Germany. johannes.schwenck@med.uni-tuebingen.de.
  • Kneilling M; Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Eberhard Karls University, Röntgenweg 13, 72076, Tübingen, Germany. johannes.schwenck@med.uni-tuebingen.de.
  • Riksen NP; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Eberhard Karls University, Tübingen, Germany. johannes.schwenck@med.uni-tuebingen.de.
  • la Fougère C; Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Eberhard Karls University, Röntgenweg 13, 72076, Tübingen, Germany.
  • Mulder DJ; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Eberhard Karls University, Tübingen, Germany.
  • Slart RJHA; Department of Dermatology, Eberhard Karls University, Tübingen, Germany.
  • Aarntzen EHJG; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
Eur J Hybrid Imaging ; 6(1): 17, 2022 Sep 01.
Article in En | MEDLINE | ID: mdl-36045228
ABSTRACT
The detection of occult infections and low-grade inflammation in clinical practice remains challenging and much depending on readers' expertise. Although molecular imaging, like [18F]FDG PET or radiolabeled leukocyte scintigraphy, offers quantitative and reproducible whole body data on inflammatory responses its interpretation is limited to visual analysis. This often leads to delayed diagnosis and treatment, as well as untapped areas of potential application. Artificial intelligence (AI) offers innovative approaches to mine the wealth of imaging data and has led to disruptive breakthroughs in other medical domains already. Here, we discuss how AI-based tools can improve the detection sensitivity of molecular imaging in infection and inflammation but also how AI might push the data analysis beyond current application toward predicting outcome and long-term risk assessment.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Eur J Hybrid Imaging Year: 2022 Document type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Eur J Hybrid Imaging Year: 2022 Document type: Article Affiliation country: Germany
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