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texrad Publications

TexRAD has featured in over 100 academic publications, won numerous awards and is currently used in over 50 prestigious institutions worldwide.

In the exciting new field of radiomics, TexRAD uncovers biomarkers in medical images which are invisible to the naked eye. Explore the innovation in TexRAD scientific research that takes place from our customers across the globe. Filter TexRAD related articles through an array of tissue types from head and neck to prostate, and learn more about the potential applications of texture analysis in lung cancer.

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Preliminary Data Using Computed Tomography Texture Analysis for the Classification of Hypervascular Liver Lesions.

Raman, S. P. et al., (2015)

Journal of Computer Assisted Tomography, 39(3), p. 1. doi: 10.1097/RCT.0000000000000217.

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Multi-parametric PET-CT in breast cancer: associations with histopathology and survival-risk’

Ganeshan, B. et al. (2015)

ECR 2015, doi: 10.1594/ecr2015/C-1320.

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Texture Analysis with Predictive Modeling of Solid Appearing Pancreatic Serous Cystadenomas versus Neuroendocrine Tumors

Verde F. et al., (2014)

Radiological Society of North America (RSNA) 2014, Chicago, USA

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Non small cell lung cancer: Efficacy of CT texture analysis in assessment of histological subtype and genotyping.

Gullo, R. et al., (2014)

Radiological Society of North America 2014 Scientific Assembly and Annual Meeting

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Role of Tumor Texture Analysis on CT Image and Tumor Metabolism Measured by FDG-PET in the Management of Non-small Cell Lung Cancer Patients.

Hayano, K. et al., (2014)

Radiological Society of North America 2014 Scientific Assembly

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CT Texture Analysis of Histologically Proven Benign and Malignant Lung Lesions.

Gullo, R. et al., (2014)

Radiological Society of North America 2014 Scientific Assembly and Annual Meeting

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The use of Quantitative Textural Analysis imaging biomarkers to predict response to temsirolimus treatment in advanced HCC subjects.

Korn, R. et al., (2014)

European Journal of Cancer. Elsevier, 50, p. 61. doi: 10.1016/S0959-8049(14)70312-0.

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Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia.

Radulescu, E. et al. (2014)

Psychiatry research, 223(3), pp. 179–86. doi: 10.1016/j.pscychresns.2014.05.014.

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