Haptic guided seeding of MRA images for semi-automatic segmentation

Abstract

We investigate how stereo graphics and haptics can be combined to facilitate the seeding procedure in semi-automatic segmentation of magnetic resonance angiography (MRA) images. Real-time volume rendering using maximum intensity projections (MIPs) has been implemented together with a haptic rendering method that provides force feedback based on local gradients and intensity values. This combination allows a user to trace vessels in the image, and to place seed-points directly in the 3D data set. Seed-regions are propagated from the seed-points according to an algorithm that favors bright voxels. An experienced user have tested the interface on whole-body MRA images with promising results. 1