A priori information in image analysis: assessment of intensity distribution for definition of shape and size of small vessels

A method for incorporating prior information in computer-based image analysis is described and critically evaluated. The specific application improves pixel resolution (spot size) and shape estimation of small vessel cross sections in exchange for dynamic range information. The potential subpixel spot size sensitivity for a 16-bit gray scale is better than one part in 32000. The performance of shape recovery is assessed in relation to signal-to-noise ratio, acquired image resolution, vessel shape complexity and aspect ratio. The process is shown to be effective and stable when the signal-to-noise ratio exceeds 10, when the number of pixels across the vessel is two or more, when the vessel contour has as many as six lobes, and when the aspect ratio is in the range 0.2-5.0.<
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