TY - GEN
T1 - Segmentation of brain MRI by adaptive mean shift
AU - Mayer, Arnaldo
AU - Greenspan, Hayit
PY - 2006
Y1 - 2006
N2 - A new automatic segmentation method for MRI images of the brain is presented, based on the adaptive mean-shift algorithm. Existing parametric methods utilize the intensity information for the segmentation task. When spatial information is introduced, parametric models may fail due to the non-convex nature of the brain tissue anatomy. A natural integration of intensity and spatial features is enabled in the non-parametric mean-shift formalism. The proposed method is validated on both simulated and real datasets.
AB - A new automatic segmentation method for MRI images of the brain is presented, based on the adaptive mean-shift algorithm. Existing parametric methods utilize the intensity information for the segmentation task. When spatial information is introduced, parametric models may fail due to the non-convex nature of the brain tissue anatomy. A natural integration of intensity and spatial features is enabled in the non-parametric mean-shift formalism. The proposed method is validated on both simulated and real datasets.
UR - https://www.scopus.com/pages/publications/33750954541
U2 - 10.1109/ISBI.2006.1624917
DO - 10.1109/ISBI.2006.1624917
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AN - SCOPUS:33750954541
SN - 0780395778
SN - 9780780395770
T3 - 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
SP - 319
EP - 322
BT - 2006 3rd IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society
T2 - 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2006
Y2 - 6 April 2006 through 9 April 2006
ER -