{ Chang2014Simultaneous,

year={ 2014 },

website={ http://www.cras2014.eu/program.html },

title={ Simultaneous Segmentation and Registration Using a Prior Model },

keywords={ ; },

author={ Chang, Ping-Lin; Stoyanov, Danail; },

abstract={ Medical image segmentation and registration are important research topics and have been studied for a long time. Unlike conventional approaches which regard the two problems independently and usually rely on image gradient, we propose a method for jointly registering a non-textured 3D model with a 2D image while segmenting it. Specifically, we use Bayesian inference to estimate the pixel-wise posterior which best fits for a prior 3D model with the 2D measurements. The approach allows the measurements not necessary to be only colour or intensity but be any kind of sensor measurement or even particularly enhanced structures. Preliminary results have shown that the probabilistic framework is very robust to noisy measurement. }

}