Assoc. Prof. Priv.-Doz. Dr. Georg Widhalm, PhD
Department of Neurosurgery
Position: Associate Professor
ORCID: 0000-0001-6014-0273
georg.widhalm@meduniwien.ac.at
Keywords
Artificial Intelligence; Brain tumor biomarkers; Digital Histopathology; Fluorescence; Intraoperative Neurophysiological Monitoring; Intraoperative Tumor Visualization; Neurooncology; Stimulated Raman Histology
Selected publications
- Wadiura, L.I. et al. (2022) ‘Toward digital histopathological assessment in surgery for central nervous system tumors using stimulated Raman histology’, Neurosurgical Focus, 53(6), p. E12. Available at: https://doi.org/10.3171/2022.9.focus22429.
- Hollon, T. et al. (2023) ‘Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging’, Nature Medicine, 29(4), pp. 828–832. Available at: https://doi.org/10.1038/s41591-023-02252-4.
- Widhalm, G. et al. (2020) ‘The value of visible 5-ALA fluorescence and quantitative protoporphyrin IX analysis for improved surgery of suspected low-grade gliomas’, Journal of Neurosurgery, 133(1), pp. 79–88. Available at: https://doi.org/10.3171/2019.1.jns182614.
- Widhalm, G. et al. (2010) ‘Value of 1H-magnetic resonance spectroscopy chemical shift imaging for detection of anaplastic foci in diffusely infiltrating gliomas with non-significant contrast-enhancement’, Journal of Neurology, Neurosurgery & Psychiatry, 82(5), pp. 512–520. Available at: https://doi.org/10.1136/jnnp.2010.205229.
- Widhalm, G. et al. (2010) ‘5‐Aminolevulinic acid is a promising marker for detection of anaplastic foci in diffusely infiltrating gliomas with nonsignificant contrast enhancement’, Cancer, 116(6), pp. 1545–1552. Available at: https://doi.org/10.1002/cncr.24903.