Affiliation: Imperial College
- Nonlinear dimensionality reduction combining MR imaging with non-imaging informationRobin Wolz
Medical Image Analysis Group, Department of Computing, Imperial College London, 180 Queen s Gate, London SW7 2AZ, UK
Med Image Anal 16:819-30. 2012..Our classification results compare favorably to what has been reported in a recent meta-analysis using established neuroimaging methods on the same database...
- LEAP: learning embeddings for atlas propagationRobin Wolz
Visual Information Processing Group, Department of Computing, Imperial College London, 180 Queen s Gate, London, SW7 2AZ, UK
Neuroimage 49:1316-25. 2010..with a greater difference between atlas and image. For the segmentation of the hippocampus on 182 images for which a manual segmentation is available, we achieved an average overlap (Dice coefficient) of 0.85 with the manual reference...
- Measurement of hippocampal atrophy using 4D graph-cut segmentation: application to ADNIRobin Wolz
Department of Computing, Imperial College London, London, UK
Neuroimage 52:109-18. 2010..Power analysis shows that 67 and 206 subjects are needed for the AD and MCI groups respectively to detect a 25% change in volume loss with 80% power and 5% significance...
- Simultaneous multi-scale registration using large deformation diffeomorphic metric mappingLaurent Risser
Institute for Mathematical Science, Imperial College, SW7 2PG, London, UK
IEEE Trans Med Imaging 30:1746-59. 2011..Results show that our method registers accurately volumetric images containing feature differences at several scales simultaneously with smooth deformations...
- Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer's diseaseKatherine R Gray
Biomedical Image Analysis Group, Department of Computing, Imperial College London, UK
Neuroimage 60:221-9. 2012..This finding may be usefully applied in the diagnosis of Alzheimer's disease, predicting disease course in individuals with mild cognitive impairment, and in the selection of participants for clinical trials...
- Hierarchical manifold learningKanwal K Bhatia
Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
Med Image Comput Comput Assist Interv 15:512-9. 2012..settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,..
- Simultaneous fine and coarse diffeomorphic registration: application to atrophy measurement in Alzheimer's diseaseLaurent Risser
Institute for Mathematical Science, Imperial College London, 53 Prince s Gate, SW7 2PG London, UK
Med Image Comput Comput Assist Interv 13:610-7. 2010..More importantly, the results also demonstrate its ability to measure shape variations at several scales simultaneously while keeping the desirable properties of LDDMM. This opens new perspectives for clinical applications...
- Multi-organ abdominal CT segmentation using hierarchically weighted subject-specific atlasesRobin Wolz
Imperial College London, London, UK
Med Image Comput Comput Assist Interv 15:10-7. 2012..Our results on a dataset of 100 CT scans compare favourable to the state-of-the-art with Dice overlap values of 94%, 91%, 66% and 94% for liver, spleen, pancreas and kidney respectively...
- Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's diseaseMaria Vounou
Statistics Section, Department of Mathematics, Imperial College London, UK
Neuroimage 60:700-16. 2012..Our findings confirmed the key role of the APOE and TOMM40 genes but also highlighted some novel potential associations with AD...
- Multi-method analysis of MRI images in early diagnostics of Alzheimer's diseaseRobin Wolz
Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
PLoS ONE 6:e25446. 2011..The most stable and reliable classification was achieved when combining all available features...