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

Author

Pearlman, Justin D. ; Leavitt, Marcia ; Newell, John B.

Author_Institution

Cardiac Comput. Center, Harvard Med. Sch., Boston, MA, USA

Volume

9

Issue

4

fYear

1990

fDate

12/1/1990 12:00:00 AM

Firstpage

461

Lastpage

465

Abstract

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

Keywords

computerised picture processing; medical diagnostic computing; patient diagnosis; a priori information; aspect ratio; computer-based image analysis; image resolution; intensity distribution; pixel resolution; signal-to-noise ratio; small vessel shape; small vessel size; subpixel spot size sensitivity; vessel contour; Biomedical imaging; Biomedical monitoring; Blood vessels; Dynamic range; Image analysis; Image resolution; Shape; Signal resolution; Signal to noise ratio; Spatial resolution;

fLanguage

English

Journal_Title

Medical Imaging, IEEE Transactions on

Publisher

ieee

ISSN

0278-0062

Type

jour

DOI

10.1109/42.61762

Filename

61762