65 citations
- King's College LondonGB2 papers
- National Hospital for Neurology and NeurosurgeryGB2 papers
- University College LondonGB2 papers
- Wellcome / EPSRC Centre for Interventional and Surgical SciencesGB2 papers
- King's College SchoolGB1 paper
- Nvidia (United Kingdom)GB1 paper
- Royal National Throat Nose and Ear HospitalGB1 paper
- Sensetime (China)CN1 paper
- University of Electronic Science and Technology of ChinaCN1 paper
2 papers
eess.IV2020★ 65 cited
Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI
Hari McGrath, Peichao Li, Reuben Dorent +6
Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. Current clinical practice is to measure the diameter of…
eess.IV2019★ 50 cited
Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss
Guotai Wang, Jonathan Shapey, Wenqi Li +7
Automatic segmentation of vestibular schwannoma (VS) tumors from magnetic resonance imaging (MRI) would facilitate efficient and accurate volume measurement to guide patient manage…