Publications

Publications

BOOKS

Di Ieva, A. (Ed.) (2016). The Fractal geometry of the brain. (Springer Series in Computational Neuroscience). New York: Springer, Springer Nature. https://doi.org/10.1007/978-1-4939-3995-4

SELECTED PEER-REVIEWED PAPERS (2019):

  • Di Ieva A. AI-Augmented Multidisciplinary Team: hype or hope? Lancet 394(10211):1801, 2019
  • Petrujkić K, Milošević N, Rajković N, Stanisavljević D, Gavrilović S, Dželebdžić D, Ilić R, Di Ieva A, Maksimović R. Computational quantitative MR image features – A potential useful tool in differentiating glioblastoma from solitary metastasis. Eur J Radiol 119:108634, 2019
  • Andronache I, Fischer R, Ahammer H, Radulović M, Ciobotaru AM, Jelinek HF, Di Ieva A, Pintilii RD, Drăghici CC, Herman GV, Nicula AS, Simion AG, Loghin V, Diaconu C, Vișan MC, Peptenatu D. Spatio-temporal evolution of forest fragmentation and connectivity using particle and fractal analysis. Sci Rep 9(1):12228, 2019
  • Grizzi F, Castello A, Qehajaj D, Russo C, Lopci E. The complexity and fractal geometry of nuclear medicine images. Mol Imaging Biol 21(3):401-409, 2019

SELECTED PAPERS (2020):

  • Liu S, Shah Z, Sav A, Russo C, Berkovsky B, Qian Y, Coiera E, Di Ieva A.  IDH status prediction in histopathology images of gliomas using deep learning. Sci Rep 10(1):7733, 2020. 
  • Di Ieva A, Russo C, Le Reste PJ, Magnussen JM, Heller G. Advanced computational and statistical multiparametric analysis of Susceptibility-Weighted Imaging to characterize gliomas and brain metastases. bioRxiv 2020; doi.org/10.1101/2020.04.24.060830
  • Jang K, Russo C, Di Ieva A. Radiomics in Gliomas: Clinical implications of computational modelling and fractal-based analysis. Neuroradiology (in Press)
  • Di Ieva A, Magnussen JS, McIntosh J, Mulcahy MJ, Pardey M, Choi C. Magnetic Resonance Spectroscopic Assessment of IDH Status in Gliomas: The New Frontiers of Spectrobiopsy in Neurodiagnostics. World Neurosurg 133:421-427, 2020
  • Dai X, Huang L, Qian Y, Xia S, Chong W, Liu J, Di Ieva A, Hou X, Ou C. Deep Learning for Automated Cerebral Aneurysm Detection on Computed Tomography Images. Int J Comput Assist Radiol Surg 15(4):715-723, 2020
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