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Biography
Dr Carlo Russo is a computer scientist and Research Associate at the Computational NeuroSurgery (CNS) Lab at Macquarie University, Sydney. He works on application and development of algorithms for image analysis in the neurosciences using non-linear geometry, including fractal analysis, and deep learning. He has previously worked more than 15 years at Humanitas Research Hospital in Rozzano, Milan (Italy), where he developed innovative software and hardware aimed to introduce computer aided automatic diagnosis tools both in research and in clinical workflows. His studies include the application of fractal geometry to histopathology and radiology images. He is author and co-author of 18 peer-reviewed articles and 5 patents
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Projects
- 1 Active
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Computational Neurosurgery Lab
Di Ieva, A., George, L., Azemi, G., Suero Molina, E., Russo, C., Liu, S., Guller, A., Tabassum, M., Kumari, P., Igrunkova, A., Unnikrishnan, S. & Beheshti, A.
1/01/19 → …
Project: Research
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A Deep Learning Framework for skull stripping in brain MRI
Tabassum, M., Suman, A. A., Russo, C., Di Ieva, A. & Liu, S., Apr 2023, IEEE EMBC 2023. Sydney: Institute of Electrical and Electronics Engineers (IEEE), 4 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open Access -
Artificial intelligence–assisted classification of gliomas using whole-slide images
Jose, L., Liu, S., Russo, C., Cong, C., Song, Y., Rodriguez, M. & Di Ieva, A., 1 Aug 2023, In: Archives of Pathology and Laboratory Medicine. 147, 8, p. 916-924 9 p.Research output: Contribution to journal › Article › peer-review
Open Access4 Citations (Scopus) -
The E3 ubiquitin ligase SCF cyclin F promotes sequestosome-1/p62 insolubility and foci formation and is dysregulated in ALS and FTD pathogenesis
Davidson, J. M., Wu, S. S. L., Rayner, S. L., Cheng, F., Duncan, K., Russo, C., Newbery, M., Ding, K., Scherer, N. M., Balez, R., García-Redondo, A., Rábano, A., Rosa-Fernandes, L., Ooi, L., Williams, K. L., Morsch, M., Blair, I. P., Di Ieva, A., Yang, S., Chung, R. S., & 1 others, Sept 2023, In: Molecular Neurobiology. 60, 9, p. 5034-5054 21 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile5 Downloads (Pure) -
Foundations of multiparametric brain tumor imaging characterization using machine learning
Jian, A., Jang, K., Russo, C., Liu, S. & Di Ieva, A., 2022, Machine learning in clinical neuroscience: foundations and applications. Staartjes, V. E., Regli, L. & Serra, C. (eds.). Switzerland: Springer, Springer Nature, p. 183-193 11 p. (Acta Neurochirurgica Supplement; vol. 134).Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
4 Citations (Scopus) -
SoftMatch: comparing scanpaths using combinatorial spatio-temporal sequences with fractal curves
Newport, R. A., Russo, C., Liu, S., Suman, A. A. & Di Ieva, A., 30 Sept 2022, In: Sensors. 22, 19, p. 1-46 46 p., 7438.Research output: Contribution to journal › Article › peer-review
Open AccessFile7 Downloads (Pure)