Search Results for author:
Found 5 papers, 0 papers with code
Local Gamma Augmentation for Ischemic Stroke Lesion Segmentation on MRI
Data augmentation techniques can compensate for a lack of training samples.
Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021
This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels.
Degenerative Adversarial NeuroImage Nets for Brain Scan Simulations: Application in Ageing and Dementia
To evaluate our approach, we trained the framework on 9852 T1-weighted MRI scans from 876 participants in the Alzheimer's Disease Neuroimaging Initiative dataset and held out a separate test set of 1283 MRI scans from 170 participants for quantitative and qualitative assessment of the personalised time series of synthetic images.
Let's agree to disagree: learning highly debatable multirater labelling
Classification and differentiation of small pathological objects may greatly vary among human raters due to differences in training, expertise and their consistency over time.
3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects
Extremely small objects (ESO) have become observable on clinical routine magnetic resonance imaging acquisitions, thanks to a reduction in acquisition time at higher resolution.
