Mean Shift
Multiparametric smoothing
by useradmin on Dec.08, 2010, under Mean Shift, Research
Multiparametric smoothing based on Mean shift procedure for ultrasound data segmentation
Segmentation of ultrasound data is improved when using multi-parametric approach. In this paper we propose the use of Multi-Parametric Mean Shift procedure (MPMS). Two derived processes are described: MPMS smoothing which achieves a multi-parametric filtering in the spatial-range domain and MPMS segmentation which takes benefit of this filtering for segmenting the multidimensional data. MPMS segmentation is particularly attractive, since it achieves an unsupervised segmentation. These methods were positively tested on three sets of simulated ultrasonic data, representative of various scatterers densities and also various scattering conditions. pdf (690kB) Poster(733kB)
Thomas Grenier, Chantal Revol-Muller, Franck Davignon, Olivier Basset, Gérard Gimenez.
Variable bandwidth mean shift
by useradmin on Dec.08, 2010, under Mean Shift, Research
Variable bandwidth Mean Shift for Smoothing ultrasonic images
As the variance of the statistics of ultrasonic data in a homogeneous tissue may be rather large and the statistics of different tissues may be very similar, a new filtering approach is proposed to enhance the contrast in ultrasonic images. It is based on the Variable Bandwidth Mean Shift algorithm adapted to the specificities of ultrasonic data. A fully automatic adaptive bandwidth selection in both range and spatial domains is described. Our method was compared to a Variable Bandwidth Mean Shift algorithm based on an adaptive range scale selection and a fixed spatial scale parameter. The results show the superiority of our method. pdf (410kB) Poster (176kB)
Thomas Grenier, Chantal Revol-Muller, Franck Davignon, Olivier Basset, Gérard Gimenez.
