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Edge-Preserving Segmentation and Fusion of Medical Images by using Enhanced Mean Shift

Irene Y.H. Gu (Institutionen för signaler och system, Signalbehandling) ; Tiesheng Wang (Institutionen för signaler och system, Signalbehandling) ; Andrew Backhouse (Institutionen för signaler och system, Signalbehandling)
Medicinteknikdagarna 2008, 14-15 oktober, Göteborg, Sweden (2008)
[Konferensbidrag, övrigt]

This paper addresses the issue of medical image segmentation by using an enhanced spatial-range mean shift. Mean shift is a method for estimating local modes (maxima) of pdf (probability density function) using a kernel-based approach. This paper describes an enhanced spatial-range mean shift segmentation method for biomedical (MRI) image segmentation. Preliminary work and the results on fusion of segmented brain images from different sensors (e.g. MRI, CT) are presented and discussed.

Nyckelord: biomedical image processing

Denna post skapades 2009-01-16.
CPL Pubid: 88175


Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling (1900-2017)


Medicinsk teknik

Chalmers infrastruktur