Abstract

JUNIOR, José Raniery Ferreira. Precision Imaging for Quantitative Analysis of Lung Neoplasms: State-of-the-Art. Acta Radiol Port [online]. 2020, vol.32, n.3, pp.9-10.  Epub July 12, 2021. ISSN 2183-1351.  https://doi.org/10.25748/arp.20799.

Methods of computerized analysis have been developed for decades, despite having limitations, to increase diagnostic accuracy as they can precisely recognize patterns in medical examinations. One alternative that has shown promising results to the community is based on quantitative radiomics assessment. Radiomics is motivated by the premise that it can reveal the underlying phenotypes of diseases captured at a macroscopic level, providing a new representation to lesions, ultimately supporting personalized medicine. In this paper, radiomic tools are explored to support that premise, finally disclosing the advance of computer- based markers and clinical decision support models for precision health care.

Keywords : Radiology; Tomography; Artificial intelligence..

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