Kolawole Oluwole Babalola

Summary

Affiliation: University of Manchester
Country: UK

Publications

  1. ncbi Comparing the similarity of statistical shape models using the Bhattacharya metric
    K O Babalola
    Division of Imaging Science and Biomedical Engineering, University of Manchester, M13 9PT, UK
    Med Image Comput Comput Assist Interv 9:142-50. 2006
  2. ncbi 3D brain segmentation using active appearance models and local regressors
    K O Babalola
    Division of Imaging Science and Biomedical Engineering, The University of Manchester, Manchester, UK
    Med Image Comput Comput Assist Interv 11:401-8. 2008
  3. ncbi Comparison and evaluation of segmentation techniques for subcortical structures in brain MRI
    K O Babalola
    Division of Imaging Science and Biomedical Engineering, University of Manchester, UK
    Med Image Comput Comput Assist Interv 11:409-16. 2008
  4. ncbi An evaluation of four automatic methods of segmenting the subcortical structures in the brain
    Kolawole Oluwole Babalola
    University of Manchester, Imaging Science and Biomedical Engineering, Stopford Building, Oxford Road, Manchester M13 9PT, UK
    Neuroimage 47:1435-47. 2009

Detail Information

Publications4

  1. ncbi Comparing the similarity of statistical shape models using the Bhattacharya metric
    K O Babalola
    Division of Imaging Science and Biomedical Engineering, University of Manchester, M13 9PT, UK
    Med Image Comput Comput Assist Interv 9:142-50. 2006
    ..We apply the technique to investigate the similarity of three models of the same 3D dataset constructed using different methods...
  2. ncbi 3D brain segmentation using active appearance models and local regressors
    K O Babalola
    Division of Imaging Science and Biomedical Engineering, The University of Manchester, Manchester, UK
    Med Image Comput Comput Assist Interv 11:401-8. 2008
    ..We evaluate the method on a large dataset, and demonstrate that it achieves results comparable with some of the best published...
  3. ncbi Comparison and evaluation of segmentation techniques for subcortical structures in brain MRI
    K O Babalola
    Division of Imaging Science and Biomedical Engineering, University of Manchester, UK
    Med Image Comput Comput Assist Interv 11:409-16. 2008
    ..Our results showed that all four methods perform on par with recently published methods. CFL performed significantly better than the other three methods according to all three classes of metrics...
  4. ncbi An evaluation of four automatic methods of segmenting the subcortical structures in the brain
    Kolawole Oluwole Babalola
    University of Manchester, Imaging Science and Biomedical Engineering, Stopford Building, Oxford Road, Manchester M13 9PT, UK
    Neuroimage 47:1435-47. 2009
    ..02, sd=0.05), indicating better agreement of each method with the gold standard than with the other methods. However, 2% of cases (mainly amygdala and nucleus accumbens) had values outside 3 standard deviations of the mean...