Contour-Based Image Registration Using Mutual Information

Airway segmentation and measurement in CT images

In this paper we describe a methodology for constructing the airways from Cone Beam CT data and representing changes before and after a medical procedure. A seed region is automatically detected for the first CT slice using a heuristic algorithm incorporating morphological filtering. Our approach then extracts relevant contours on 3D slices by using gradient vector flow (GVF) snakes, modified by an edge detection and snake-shifting step. Following this, a 3D model is constructed. We then estimate the volume of the airway based on segmented 3D shape.

Measuring and evaluating ground truth for boundary detection in medical images

In this paper we describe a methodology for measuring the ground truth for boundary detection methods in medical images. An interface is used to allow medical experts to outline boundaries of interest on images. Following this, the accuracy of the experts in repeating the ground truth detection process is evaluated. Finally, an approach is described for comparing the ground truth as provided by experts with actual boundaries detected automatically. Experimental results are presented to validate the proposed algorithms.