Can we trust the calculation of texture indices of CT images? A phantom study

Imaging Heterogeneity in Lung Cancer: Techniques, Applications, and Challenges

(2016) Usman Bashir et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Imaging biomarker roadmap for cancer studies

(2016) James P. B. O'Connor et al.   Nature Reviews Clinical Oncology

Radiomics: Images Are More than Pictures, They Are Data

(2016) Robert J. Gillies et al.   RADIOLOGY

Preliminary investigation into sources of uncertainty in quantitative imaging features

(2015) Xenia Fave et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Measuring Computed Tomography Scanner Variability of Radiomics Features

(2015) Dennis Mackin et al.   INVESTIGATIVE RADIOLOGY

Tumor Texture Analysis in PET: Where Do We Stand?

(2015) I. Buvat et al.   JOURNAL OF NUCLEAR MEDICINE

Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

(2015) Xenia Fave et al.   MEDICAL PHYSICS

18F-FDG PET-Derived Textural Indices Reflect Tissue-Specific Uptake Pattern in Non-Small Cell Lung Cancer

(2015) Fanny Orlhac et al.   PLoS One

Exploring Variability in CT Characterization of Tumors: A Preliminary Phantom Study

(2014) Binsheng Zhao et al.   Translational Oncology

Reproducibility and Prognosis of Quantitative Features Extracted from CT Images

(2014) Yoganand Balagurunathan et al.   Translational Oncology

Exploring intra- and inter-reader variability in uni-dimensional, bi-dimensional, and volumetric measurements of solid tumors on CT scans reconstructed at different slice intervals

(2013) Binsheng Zhao et al.   EUROPEAN JOURNAL OF RADIOLOGY

High quality machine-robust image features: Identification in nonsmall cell lung cancer computed tomography images

(2013) Luke A. Hunter et al.   MEDICAL PHYSICS