  Images conveniently capture the result of physical processes, representing
rich source of information for data driven medicine, engineering, and science.
The modeling of an image as a graph allows the application of graph-based
algorithms for content analysis. Amongst these, one of the most used is the
Dijkstra Single Source Shortest Path algorithm (DSSSP), which computes the path
with minimal cost from one starting node to all the other nodes of the graph.
However, the results of DSSSP remains unknown for nodes until they are
explored. Moreover, DSSSP execution is associated to frequent jumps between
distant locations in the graph, which results in non-optimal memory access,
reduced parallelization, and finally increased execution time. Therefore, we
propose AnyDijkstra, an iterative implementation of the Dijkstra SSSP algorithm
optimized for images, that retains anytime properties while accessing memory
following a cache-friendly scheme and maximizing parallelization.
