Image segmentation via motion vector estimates

Aiman Albert Abdel-Malek; Orkun Hasekioglu; John J. Bloomer

doi:10.1117/12.18932

1 July 1990 Image segmentation via motion vector estimates

Aiman Albert Abdel-Malek, Orkun Hasekioglu, John J. Bloomer

Proceedings Volume 1233, Medical Imaging IV: Image Processing; (1990) https://doi.org/10.1117/12.18932
Event: Medical Imaging '90, 1990, Newport Beach, CA, United States

Abstract

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.

Citation Download Citation

Aiman Albert Abdel-Malek, Orkun Hasekioglu, and John J. Bloomer "Image segmentation via motion vector estimates", Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); https://doi.org/10.1117/12.18932

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