Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
We propose the use of eigenvectors for automated multidimensional image segmentation. The approach of Shi and Malik [8] has been extended in three dimensions and applied on biomed...
This paper presents a novel solution to the High Dynamic Range (HDR) image compression problem using level set framework. Using level set framework, this method separates the HDR ...
A novel approach to the X-ray tomography problem with sparse projection data is proposed. Non-negativity of the X-ray attenuation coefficient is enforced by modelling it as max{(x)...