Publications

BOOKS

Di Ieva A, Suero Molina E, Liu S, Russo C. (Eds). (2024). Computational Neurosurgery. Springer, 2024.

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

2nd  Edition (2024):

Book chapter in Machine Learning in Clinical Neuroscience (Springer, 2021): Jian A, Jang K, Russo C, Liu S, Di Ieva A. Foundations of multiparametric brain tumour imaging characterisation using machine learning. pp 183-193

The Mathematical Engineering of Deep Learning (Liquet B. et al).

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):

• Russo C, Liu S, Di Ieva A. Impact of spherical coordinates transformation pre-processing in Deep Convolutional Neural Networks for brain tumor segmentation and survival prediction. arXiv:2010.2010.13967, 27 October 2020
• Gao Y, Xiao X, Han B, Li G, Ning X, Wang D, Cai W, Kikinis R, Berkovsky S, Di Ieva A, Zhang L, Ji N, Liu S. A Deep Learning methodology for differentiating glioma recurrence from radiation necrosis using multimodal MRI: Algorithm development and validation. JMIR Med Inform 8(11):e19805, 2020.
• Russo C, Liu S, Di Ieva A. Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI. arXiv:2008.07090, 17 Aug 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 62(7):771-790, 2020
• 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

SELECTED PAPERS (2021):

• Di Ieva A, Russo C, Al Suman A, Liu S. Computational Neurosurgery in brain tumors: A paradigm shift on the use of Artificial Intelligence and Connectomics in pre- and intra-operative imaging. Neuro-Oncology 23(Suppl 6):vi227, 2021.
• Al Suman A, Russo C, Carrigan A, Nalepka P, Liquet-Weiland B, Newport RA, Kumari P, Di Ieva A. Spatial and time-domain analysis of eye-tracking during screening of brain MRIs. Plos One 16(12):e260717, 2021
• Russo C, Liu S, Di Ieva A. Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI. Medical & Biological Engineering & Computing (in Press), Github Repository: https://github.com/doc78/CartesianToSphericalMRI
• Koong K, Preda V, Jian A, Liquet-Weiland B, Di Ieva A. Application of artificial intelligence and radiomics in pituitary neuroendocrine and sellar tumours: A quantitative and qualitative synthesis. Neuroradiology (in Press)
• Newport RA, Russo C, Al Suman A, Di Ieva A. Assessment of the eye-tracking Scanpath outliers using fractal geometry. Heliyon 7(7):E07616, 2021
• Di Ieva A, Rosenfeld JV, Stoodley MA. The Royal Australasian College of Surgeons John Mitchell Crouch Fellowship: A neurosurgical perspective. ANZ J Surg 91(5):793-794, 2021
• Liu S, Meng T, Russo C, Di Ieva A, Berkovsky S, Peng L, Dou W, Qian L. Brain volumetric and fractal analysis of synthetic MRI: A comparative study with conventional 3D T1-weighted images. Eur J Radiol 141:109782, 2021
• Jose L, Liu S, Russo C, Nadort A, Di Ieva A. Generative Adversarial Networks in Digital Pathology: A review on histopathological image processing. Journal of Pathology Informatics 12:43, 2021
• Di Ieva A, Russo C, Liu S, Jian A, Bai MY, Qian Y, Magnussen JM. Application of Deep Learning for automatic segmentation of brain tumors on Magnetic Resonance Imaging: A heuristic approach in the clinical scenario. Neuroradiology 63;1253-1262, 2021
• Jian A, Jang K, Manuguerra M, Liu S, Magnussen J, Di Ieva A. Machine learning for the prediction of molecular markers in glioma on magnetic resonance imaging: A systematic review and meta-analysis. Neurosurgery 89(1):31-44, 2021
• Russo C, Liu S, Di Ieva A. Impact of spherical coordinates transformation pre-processing in Deep Convolutional Neural Networks for brain tumor segmentation and survival prediction. BrainLes: International MICCAI Brainlesion Workshop, Lima - Peru, October 4, 2020. Published in Brainlesion: Glioma, multiple sclerosis, stroke, and traumatic brain injuries. March 2021, pp. 295-306
• Al Suman A, Sarda S, Asikuzzaman Md, Webb AL, Perriman MD,  Tahtali M, Di Ieva A, Pickering MR.  Two-stage U-Net++ for Medical Image Segmentation. 2021 Digital Image Computing: Techniques and Applications (DICTA), IEEE Xplore, December 2021

SELECTED PAPERS (2022):

• Zueva MV, Di Ieva A, Pyankova SD. Editorial: Fractals in the diagnosis and treatment of the retina and brain diseases. Front Netw Physiol 2:1054439, 2022.
• Di Ieva A. Debunking the debulking in glioma surgery. Neurooncol Pract. 26;10(1):104-105, 2022
• Newport RA, Russo C, Liu S, Al Suman A, Di Ieva A. Comparing scanpaths using combinatorial spatio-temporal
  sequences with fractal curves. Sensors 22(10):7438, 2022
• Unnikrishnan S, Jose L, Liu S, Di Ieva A. Intra- and post-operative artificial intelligence strategies for brain tumor diagnosis in computational digital neuropathology. Book chapter in: Artificial Intelligence strategies for brain tumor diagnosis: postoperative analysis. Editor: El-Baz, AY. Elsevier Published 2022 (in Press)
• Cong C, Liu S, Di Ieva A, Pagnucco M, Berkovsky S, Song Y. Stain normalisation of histopathology images with semi-supervised generative networks. Medical Image Analysis 82:102580, 2022
• Jose L, Liu S, Russo C, Cong C, Song Y, Rodriguez M, Di Ieva A. Artificial intelligence-assisted classification of gliomas using whole-slide images. Arch Pathol Lab Med. 147(8):916-924, 2023
• Jian A, Liu S, Di Ieva A. Artificial Intelligence for survival prediction in brain tumors on neuroimaging. Neurosurgery 91(1):8-26, 2022
• Tanaka K, Russo C, Liu S, Stoodley MA, Di Ieva A. Use of deep learning in the MRI diagnosis of Chiari malformation type I. Neuroradiology 64*8):1585-1592, 2022
• Jian A, Jang K, Russo C, Liu S, Di Ieva A. Foundations of multiparametric brain tumour imaging characterisation using machine learning. Acta Neurochir Suppl 134:183-193, 2022

SELECTED PAPERS (2023):

• Black D, Byrne D, Walke A, Liu S, Di Ieva A, Stummer W, Salcudean T, Suero Molina A. Machine learning-based spectroscopic tissue differentiation in fluorescence-guided neurosurgery. Neuro-oncology 24, Supplement 5, p. 161-162, INNV-24, 2023
• Chitnis SR, Liu S, Dash T, Verlekar TT, Di Ieva A, Berkovsky S, Vig L, Srinivasan A. Domain-specific pre-training improves confidence in whole slide image classification. Annu Int Conf IEEE Eng Med Biol Soc. 1-4, 2023.  doi: 10.1109/EMBC40787.2023.10340659.
• Suero Molina E, Black D, Walke A, Azemi G, D'Alessandro F, Koenig S, Stummer W. Unraveling the blue shift in porphyin fluorescence in glioma: The 620 nm peak and its potential significance in tumor biology. Front Neurosci 17:1261679, 2023.
• Tabassum M, Al Suman A, Russo C, Di Ieva A, Liu S. A Deep Learning framework for skull stripping in brain MRI. Annu Int Conf  IEEE Eng Med Biol Soc. 1-4, 2023. doi: 10.1109/EMBC40787.2023.10340846.
• Suero Molina E, Tait MJ, Di Ieva A. Connectomics as a prognostic tool of functional outcome in glioma surgery of the supplementary motor area: illustrative case. J Neurosurg Case Lessons. 6(6):CASE23286, 2023
• Vaezzadeh M, Kachooei E, Krishnamurthy S, Manandhar P, Nadort A, Guillemin GJ, Di Ieva A, Santiago M, Heng B, Guller A. Combination drug therapy of glioblastoma: Lessons from 3D in vitro models and the roadmap for future research. Advanced Therapeutics 6(11):2300197, 2023
• Anokwute MC, Christodoulides A, Campbell RG, Harvey RH, Di Ieva A. Robotics for approaches to the anterior cranial fossa. Book Chapter in “Robotics in Skull Base Surgery”, Editors Al-Salihi M et al.. Springer Publisher, 2023
• Tabassum M, Al Suman A, Suero Molina E, Pan E, Di Ieva A, Liu S. Radiomics and Machine Learning in Brain Tumors and Their Habitat: A systematic review. Cancers 15(15):3845, 2023
• Anokwute MC, Preda V, Di Ieva A. Determining contemporary barriers to effective multidisciplinary team meetings in neurological surgery: A review of the literature. World Neurosurg 172:73-80, 2023
• Davidson JM, Rayner SL, Liu S, Cheng F, Di Ieva A, Chung RS, Lee A. Inter-regional proteomic profiling of the human brain using an optimized protein extraction method from formalin-fixed tissue to identify signaling pathways. Int J Mol Sci 24(5):4283, 2023
• Peptenatu D, Andronache I, Helmut A, Radulovic M, Costanza JK, Jelinek H, Di Ieva A, Koyama K, Grecu A, Gruia AK, Simion AG, Nadelcu ID. A new fractal index to classify forest fragmentation and disorder. Landscape Ecology 38(6):1373-1393, 2023
• Davidson JM, Wu SSL, Rayner SL, Cheng F, Duncan K, Russo C, Newbery M, Ding K, Scherer NM, Balez R, García-Redondo A, Rábano A, Rosa-Fernandes L, Ooi L, Williams KL, Morsch M, Blair IP, Di Ieva A, Yang S, Lee A. The E3 Ubiquitin ligase SCF Cyclin F promotes Sequestosome-1/p62 insolubility and foci formation and is dysregulated in ALS and FTD pathogenesis. Mol Neurobiol 60(9):5034-5054, 2023.
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SELECTED PAPERS (2024):

Black D, Byrne D, Walke A, Liu S, Di Ieva A, Kaneko S, Stummer W, Salcudean T, Suero Molina E. Towards machine learning-based quantitative hyperspectral image guidance for brain tumor resection. Commun Med 4(1):131, 2024

King V, Liu S, Russo C, Jayasekara M, Stoodley M, Di Ieva A. Use of Artificial Intelligence in the prediction of Chiari Malformation type 1 recurrence after posterior fossa decompressive surgery. Cureus 16(5):e60879, 2024

Cong C, Liu S, Rana P, Pagnucco M, Di Ieva A, Berkovsky S, Song Y. Adaptive unified contrastive learning with graph-based feature aggregator for imbalanced medical image classification. Expert Systems with Applications 251:123783, 2024

Livi L, Sadeghian A, Di Ieva A. Fractal geometry meets computational intelligence: Future perspectives. Adv Neurobiol 36:983-997, 2024

Rinzivillo C, Kaleagasioglu F, Casciaro F, Scoppa F, Marvulli R, Ware K, Conte E, Di Ieva A. An experimental verification of neurophysics treatment by executing a multifractal analysis of surface electromiography signals on trapezius, abdominals, and adductor muscles in athletes. Complexity Science in Human Change 81-117, 2024

Andronache I, Peptenatu D, Ahammer H, Radulovic M, Djuričić GJ, Jelinek HF, Russo C, Di Ieva A. Fractals in the neurosciences: A translational geographical approach. Adv Neurobiol 36:953-981, 2024

Newport RA, Liu S, Di Ieva A. Analyzing eye paths using fractals. Adv Neurobiol 36:827-848, 2024

Di Ieva A. Computational and translational fractal-based analysis in the translational neurosciences: An overview. Adv Neurobiol 36:781-793, 2024

Di Ieva A., Al-Kadi O. Computatoinal fractal-based analysis of brain tumor microvascular networks. Adv Neurobiol 36:525-544, 2024

Al-Kadi O, Di Ieva A. Fractal-based analysis of histological features of brain tumors. Adv Neurobiol 36:501-524, 2024

Di Ieva A. Computational fractal-based analysis of MR Susceptibility-Weighted Imaging (SWI) in neuro-oncology and neurotraumatology. Adv Neurobiol 36:445-468, 2024

Lahmiri S, Boukadoum M, Di Ieva A. Fractals in neuroimaging. Adv Neurobiol 36:429-444, 2024

Di Ieva A, Reishofer G. Fractal-based analysis of arteriovenous malformations (AVMs). Adv Neurobiol 36:413-428, 2024

Davidson JM, Zhang L, Yue GH, Di Ieva A. Fractal dimension studies of the brain shape in aging and neurodegenerative diseases. Adv Neurobiol 36:329-329, 2024

Díaz Beltrán L, Madan CR, Finke C, Krohn S, Di Ieva A, Esteban FJ. Fractal dimension analysis in neurological disorders: An overview. Adv Neurobiol 36:313-328, 2024

Di Ieva A. Fractals, pattern recognition, memetics, and AI: A personal journey in the computational neurosurgery. Adv Neurobiol 36:273-283, 2024

Di Ieva A. Fractal analysis in clinical neurosciences: An overview. Adv Neurobiol 36:261-271,  2024

Di Ieva A. Fractals in Neuroanatomy and Basic Neurosciences: An overview. Adv. Neurobiol 36:141-147, 2024

Porcaro C, Moaveninejad S, D'Onofrio V, Di Ieva A. Fractal Time Series: Background, estimation methods, and performances. Adv Neurobiol 36:95-137, 2024

Di Ieva A. The Fractal Geometry of the Brain: An Overview. Adv Neurobiol 36:3-13, 2024

Moradizeyveh S, Tabassum M, Liu S, Newport RA, Beheshti A, Di Ieva A. When eye-tracking meets machine learning: A systematic review on applications in medicla image analysis. arXiv: 2403.07834v1, 12 March 2024

• Wesselink EO, Elliott JM, Pool-Goudzwaard A, Pevenage PP, Di Ieva A, Weber II KA. Quantifying lumbar paraspinal intramuscular fat: Accuracy and reliability of automated thresholding models. NASSJ 17, 100313, 2024
• Tavoosi P, Azemi G, Sowman PF. Decoding of auditory surprise in adult magnetoencephalography data using Bayesian models. Digital Signal Processing. 2024 Mar 1:104450