In this paper, we propose a hybrid similarity measure for 2D-3D image registration that is a weighted combination of an intensitybased image similarity measure and a point-based me...
Daniel B. Russakoff, Torsten Rohlfing, Ramin Shahi...
Abstract. We propose a novel approach to landmark-based medical image registration based on the geostatical method of Kriging prediction. Our method exploits the spatial statistica...
This paper describes a new robust and fully automatic method for calibration of three-dimensional (3D) freehand ultrasound. 3D Freehand ultrasound consists in mounting a position s...
Abstract. This paper evaluates strategies to combine multiple segmentations of the same image, generated for example by different segmentation methods or by different human experts...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
Abstract. We present a novel technique where a medical image segmentation system is evolved using genetic programming. The evolved system was trained on just 8 images outlined by a...
Given models for healthy brains, tumor segmentation can be seen as a process of detecting abnormalities or outliers that are present with certain image intensity and geometric prop...
Marcel Prastawa, Elizabeth Bullitt, Sean Ho, Guido...
Abstract. In this paper we present a new algorithm for 3D medical image segmentation. The algorithm is fast, relatively simple to implement, and semi-automatic. It is based on mini...
In this paper we introduce user-defined segmentation constraints within the level set methods. Snake-driven methods are powerful and widely explored techniques for object extractio...
Abstract. Most intensity-based fMRI registration methods do not account for the fact that the volumes being aligned may differ: one may have blood oxygen level dependent (BOLD) con...