Milea Timbergen

149 Supplemental References 1 . Vos M, Starmans MPA, Timbergen MJM, et al. Radiomics approach to distinguish between well differentiated liposarcomas and lipomas on MRI. Br J Surg 2019;106(13):1800-9. 2 . Starmans MPA. Workflow for Optimal Radiomics Classification (WORC) 2020 [Available from: https:// github.com/MStarmans91/WORC. 3 . van der Voort SR, Starmans MPA. Predict a Radiomics Extensive Differentiable Interchangable Classification Toolkit (PREDICT) 2018 [Available from: https://github.com/Svdvoort/PREDICTFastr. 4 . Van Griethuysen JJ, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, et al. Computational radiomics system to decode the radiographic phenotype. Cancer research. 2017;77(21):e104-e107. 5. GitHub Code for feature extraction, model creation and evaluation. http://doi.org/10.5281/ zenodo.4017191 [accessed September 7, 2020] 6 . Zwanenburg A, Vallières M, Abdalah M, Aerts H, Andrearczyk V, Apte A, et al. The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping. Radiology. 2020;295:191145. 7 . M.P.A. Starmans, DMRadiomics, 2020. http://doi.org/10.5281/zenodo.4017191. [accessed September 7, 2020] 8 . Frangi AF, Niessen WJ, Vincken KL, Viergever MA. Multiscale vessel enhancement filtering. In: Wells WM, Colchester A, Delp S, editors. Medical Image Computing and Computer-Assisted Intervention (MICCAI); 1998; Berlin, Heidelberg: Springer Berlin Heidelberg; 1998. p. 130-137. 9 . Kovesi P, editor Phase congruency detects corners and edges. The Australian pattern recognition society conference: DICTA; 2003 2003. 10 . Han H, Wang W-Y, Mao B-H. Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning. 2005:878-887. 5

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