Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis

By S. Chicklore, V. Goh, M. Siddique, Arunabha Roy, P. Marsden, G. Cook. European Journal of Nuclear Medicine and Molecular Imaging, 2012

492 citations recorded by the source corpus.

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Characterization of PET/CT images using texture analysis: the past, the present… any future? (2016, methodology): “As a multimodal imaging modality, PET/CT is a promising tool for noninvasive exploration of intratumour heterogeneity at the macroscopic scale in both the anatomical and functional dimensions [2, 3].”
Repeatability and Reproducibility of Radiomic Features: A Systematic Review (2018, unknown): “Recent studies have suggested that complex shape metrics and the nonuniform appearance of the tumor mass in images (ie, texture) also provide information about the likely outcome of the disease (3, 10-12).”
The role of quantitative PET in predicting cancer treatment outcomes (2014, methodology): “Among these methods, statistical approaches based on the co-occurrence matrix and its variants such as the gray level co-occurrence matrix (GLCM), neighborhood gray tone difference matrix (NGTDM), run-length matrix (RLM), and gray level size-zone matrix (GLSZM) have been widely applied for character”
The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges (2019, background): “In addition, wavelet features, referred to as multiresolution image scaling features, and fractals, referred to as model-based features, were also used a lot in radiomic studies [63-65].”