Image segmentation via motion vector estimates

In the visual world moving edges in the periphery represent vital pieces of information that directs the human foveation mechanism to selectively gather information around these specific locations. This computationally efficient approach of allocating resources at key locations has inspired computer visionists to develop new target detection and hacking algorithms based on motion detection in image sequences. In this study we implemented a recursive algorithm for estimating motion vector fields for each pixel in a sequence of Digital Subtraction Angiography (DSA) images. Velocity information is used to segment the image and perform linear quadratic and acceleration-based frame interpolation to produce an apparent frame rate increase. Our results demonstrate the feasibility of low-rate digital fluoroscopy hence less exposure risks while preserving image quality. Furthermore the technique can be useful in the medical Picture Archival and Communication Systems (PACS) where image data can be compressed by storing and transmiting only the motion fields associated with the moving pixels. 1.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.