- Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. 2016;278(2):563-77. doi: 10.1148/radiol.2015151169. PubMed PMID: 26579733. PubMed PMCID: PMC4734157.
- Soleymani Y, Jahanshahi AR, Hefzi M, Fazel Ghaziani M, Pourfarshid A, Khezerloo D. Evaluation of textural-based radiomics features for differentiation of COVID-19 pneumonia from non-COVID pneumonia. Egyptian Journal of Radiology and Nuclear Medicine. 2021;52:1-7.
- Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, Van Stiphout RG, Granton P, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441-6. doi: 10.1016/j.ejca.2011.11.036. PubMed PMID: 22257792. PubMed PMCID: PMC4533986.
- Haarburger C, Müller-Franzes G, Weninger L, Kuhl C, Truhn D, Merhof D. Radiomics feature reproducibility under inter-rater variability in segmentations of CT images. Sci Rep. 2020;10(1):12688. doi: 10.1038/s41598-020-69534-6. PubMed PMID: 32728098. PubMed PMCID: PMC7391354.
- Soleymani Y, Jahanshahi AR, Pourfarshid A, Khezerloo D. Reproducibility assessment of radiomics features in various ultrasound scan settings and different scanner vendors. J Med Imaging Radiat Sci. 2022;53(4):664-71. doi: 10.1016/j.jmir.2022.09.018. PubMed PMID: 36266173.
- Cho HH, Lee SH, Kim J, Park H. Classification of the glioma grading using radiomics analysis. 2018;6:e5982. doi: 10.7717/peerj.5982. PubMed PMID: 30498643. PubMed PMCID: PMC6252243.
- Jang K, Russo C, Di Ieva A. Radiomics in gliomas: clinical implications of computational modeling and fractal-based analysis. Neuroradiology. 2020;62(7):771-90. doi: 10.1007/s00234-020-02403-1. PubMed PMID: 32249351.
- Singh G, Manjila S, Sakla N, True A, Wardeh AH, Beig N, et al. Radiomics and radiogenomics in gliomas: a contemporary update. Br J Cancer. 2021;125(5):641-57. doi: 10.1038/s41416-021-01387-w. PubMed PMID: 33958734. PubMed PMCID: PMC8405677.
- Xie T, Chen X, Fang J, Kang H, Xue W, Tong H, et al. Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading. J Magn Reson Imaging. 2018;47(4):1099-111. doi: 10.1002/jmri.25835. PubMed PMID: 28845594.
- Kobayashi K, Miyake M, Takahashi M, Hamamoto R. Observing deep radiomics for the classification of glioma grades. Sci Rep. 2021;11(1):10942. doi: 10.1038/s41598-021-90555-2. PubMed PMID: 34035410. PubMed PMCID: PMC8149679.
- Chaddad A, Sabri S, Niazi T, Abdulkarim B. Prediction of survival with multi-scale radiomic analysis in glioblastoma patients. Med Biol Eng Comput. 2018;56(12):2287-300. doi: 10.1007/s11517-018-1858-4. PubMed PMID: 29915951.
- Bae S, Choi YS, Ahn SS, Chang JH, Kang SG, Kim EH, et al. Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction. 2018;289(3):797-806. doi: 10.1148/radiol.2018180200. PubMed PMID: 30277442.
- Qin JB, Liu Z, Zhang H, Shen C, Wang XC, Tan Y, et al. Grading of Gliomas by Using Radiomic Features on Multiple Magnetic Resonance Imaging (MRI) Sequences. Med Sci Monit. 2017;23:2168-78. doi: 10.12659/msm.901270. PubMed PMID: 28478462. PubMed PMCID: PMC5436423.
- Jeong J, Wang L, Ji B, Lei Y, Ali A, Liu T, et al. Machine-learning based classification of glioblastoma using delta-radiomic features derived from dynamic susceptibility contrast enhanced magnetic resonance images: Introduction. Quant Imaging Med Surg. 2019;9(7):1201-13. doi: 10.21037/qims.2019.07.01. PubMed PMID: 31448207. PubMed PMCID: PMC6685811.
- Das IJ, Andersen A, Chen ZJ, Dimofte A, Glatstein E, Hoisak J, et al. State of dose prescription and compliance to international standard (ICRU-83) in intensity modulated radiation therapy among academic institutions. Pract Radiat Oncol. 2017;7(2):e145-55. doi: 10.1016/j.prro.2016.11.003. PubMed PMID: 28274405.
- Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, et al. The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository. J Digit Imaging. 2013;26(6):1045-57. doi: 10.1007/s10278-013-9622-7. PubMed PMID: 23884657. PubMed PMCID: PMC3824915.
- Beer JC, Tustison NJ, Cook PA, Davatzikos C, Sheline YI, Shinohara RT, et al. Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data. 2020;220:117129. doi: 10.1016/j.neuroimage.2020.117129. PubMed PMID: 32640273. PubMed PMCID: PMC7605103.
- Da-Ano R, Masson I, Lucia F, Doré M, Robin P, Alfieri J, et al. Performance comparison of modified ComBat for harmonization of radiomic features for multicenter studies. Sci Rep. 2020;10(1):10248. doi: 10.1038/s41598-020-66110-w. PubMed PMID: 32581221. PubMed PMCID: PMC7314795.
- Bettinelli A, Branchini M, De Monte F, Scaggion A, Paiusco M. Technical Note: An IBEX adaption toward image biomarker standardization. Med Phys. 2020;47(3):1167-73. doi: 10.1002/mp.13956. PubMed PMID: 31830303.
- Di Leo G, Sardanelli F. Statistical significance: p value, 0.05 threshold, and applications to radiomics-reasons for a conservative approach. Eur Radiol Exp. 2020;4(1):18. doi: 10.1186/s41747-020-0145-y. PubMed PMID: 32157489. PubMed PMCID: PMC7064671.
- Toubiana D, Maruenda H. Guidelines for correlation coefficient threshold settings in metabolite correlation networks exemplified on a potato association panel. BMC Bioinformatics. 2021;22(1):116. doi: 10.1186/s12859-021-03994-z. PubMed PMID: 33691629. PubMed PMCID: PMC7945624.
- Xiong Z, Cui Y, Liu Z, Zhao Y, Hu M, Hu J. Evaluating explorative prediction power of machine learning algorithms for materials discovery using k-fold forward cross-validation. Computational Materials Science. 2020;171:109203. doi: 10.1016/j.commatsci.2019.109203.
- Togao O, Hiwatashi A, Yamashita K, Kikuchi K, Mizoguchi M, Yoshimoto K, et al. Differentiation of high-grade and low-grade diffuse gliomas by intravoxel incoherent motion MR imaging. Neuro Oncol. 2016;18(1):132-41. doi: 10.1093/neuonc/nov147. PubMed PMID: 26243792. PubMed PMCID: PMC4677415.
- Zhao SS, Feng XL, Hu YC, Han Y, Tian Q, Sun YZ, et al. Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist’s reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images. BMC Neurol. 2020;20(1):48. doi: 10.1186/s12883-020-1613-y. PubMed PMID: 32033580. PubMed PMCID: PMC7007642.
- Zacharaki EI, Wang S, Chawla S, Soo Yoo D, Wolf R, et al. Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme. Magn Reson Med. 2009;62(6):1609-18. doi: 10.1002/mrm.22147. PubMed PMID: 19859947. PubMed PMCID: PMC2863141.
- Sun L, Zhang S, Chen H, Luo L. Brain Tumor Segmentation and Survival Prediction Using Multimodal MRI Scans With Deep Learning. Front Neurosci. 2019;13:810. doi: 10.3389/fnins.2019.00810. PubMed PMID: 31474816. PubMed PMCID: PMC6707136.
|