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Radiomics in Oncological PET/CT: a Methodological Overview / 대한핵의학회잡지
Korean Journal of Nuclear Medicine ; : 14-29, 2019.
Article in English | WPRIM | ID: wpr-786452
ABSTRACT
Radiomics is a medical imaging analysis approach based on computer-vision. Metabolic radiomics in particular analyses the spatial distribution patterns of molecular metabolism on PET images. Measuring intratumoral heterogeneity via image is one of the main targets of radiomics research, and it aims to build a image-based model for better patient management. The workflow of radiomics using texture analysis follows these

steps:

1) imaging (image acquisition and reconstruction); 2) preprocessing (segmentation & quantization); 3) quantification (texture matrix design & texture feature extraction); and 4) analysis (statistics and/or machine learning). The parameters or conditions at each of these steps are effect on the results. In statistical testing or modeling, problems such as multiple comparisons, dependence on other variables, and high dimensionality of small sample size data should be considered. Standardization of methodology and harmonization of image quality are one of the most important challenges with radiomics methodology. Even though there are current issues in radiomics methodology, it is expected that radiomics will be clinically useful in personalized medicine for oncology.
Subject(s)

Full text: Available Index: WPRIM (Western Pacific) Main subject: Population Characteristics / Diagnostic Imaging / Sample Size / Precision Medicine / Positron Emission Tomography Computed Tomography / Metabolism Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Korean Journal of Nuclear Medicine Year: 2019 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Population Characteristics / Diagnostic Imaging / Sample Size / Precision Medicine / Positron Emission Tomography Computed Tomography / Metabolism Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Korean Journal of Nuclear Medicine Year: 2019 Type: Article