Scholar
Navodini Wijetilake
Google Scholar ID: STvTJhYAAAAJ
King's College London
Citations & Impact
Citations
462
H-index
10
i10-index
10
Publications
20
Co-authors
14
list available
Contact
Resume
Academic Achievements
- - Published an article on the real-world impact of fully automated volume measures of vestibular schwannoma
- - Co-authored a conference paper on clinically guided automated linear feature extraction for vestibular schwannoma in 'Medical Imaging 2024: Image Processing'
- - Collaborated on a study published in 'Frontiers in Computational Neuroscience' about deep learning for automatic segmentation of vestibular schwannoma
- - Completed a systematic review on imaging biomarkers for extra-axial intracranial tumors
Research Experience
- - Worked on the real-world impact of fully automated volume measures of vestibular schwannoma on the evaluation of size change and clinical management outcomes in a multidisciplinary meeting setting
- - Involved in research on deep learning methods for automatic segmentation of vestibular schwannoma from multi-center routine MRI
- - Conducted a systematic review on imaging biomarkers associated with extra-axial intracranial tumors
Background
- - Research Interests: Neuroscience, Magnetic Resonance Imaging, Automatic Segmentation, Clinical Guidelines
- - Professional Field: Acoustic Neuroma, Imaging Biomarkers for Intracranial Tumors
Miscellany
- - Contributed to UN Sustainable Development Goals
