Hybrid-reality: collaborative biomedical data exploration exploiting 2-D and 3-D correspondence.

Abstract

Doctors and radiologists are trained to infer and interpret three-dimensional information from two-dimensional images. Traditionally, they analyze sets of two-dimensional images obtained from imaging systems based on x-rays, computed tomography, and magnetic resonance. These images correspond to slices or projections to a single plane. With the resolution of the scanners increasing in all directions, so is the complexity of the data that can be used for diagnostic purposes. Using volume rendering techniques, massive stacks of image slices can be combined into a single image and important features stressed, increasing the doctor's ability to extract useful information from the image. A hybrid visualization approach combining 2D slices and 3D visuals is presented, drawing from the best features of both of these approaches. 2D slices emulate conventional medical images while 3D images provide additional information, such as better spatial location of the features in the surrounding structures as well as the 3D shape of features.