RESUMEN
Few networks offer sufficient bandwidth for the transmission of high resolution two- and three-dimensional medical image sets without incurring significant latency. Traditional compression methods achieve bit-rate reduction based on pixel statistics and ignore visual cues that are important in identifying visually informative regions. This paper describes an approach to managing image transmission in which spatial regions are selected and prioritized for transmission so that visually informative data is received in a timely manner. This context-based image transmission (CBIT) scheme is a lossless form of progressive image transmission (PIT) in which gross structure, represented by an approximate iconic image, is transmitted first. Each part of this iconic image is progressively updated, using a simple set of rules that take into account viewing requirements. CBIT is realized using knowledge about image composition to segment, label, prioritize, and fit geometric models to regions of an image. Tests, using neurological images, show that, with CBIT, a valuable transmitted image is received with a latency that is about one-tenth that of traditional PIT schemes. Frequently, the necessary regions of the image are transmitted in about half the time taken to transmit the full image.