Abstract

Image analysis (IA) knowledge and scene analysis (SA) knowledge are cojointly used in Medical Image Interpretation (MII). Usually knowledge is implicitly incorporated into procedures, making the latter very application-dependent. On the contrary, we want to clearly separate them in the MII system we are designing. For this purpose, we selected the evaluation of the functional pulmonary fraction on SPECT images as a case example from which we characterized: (1) image analysis knowledge: -- the manipulated IA objects are identified and organized in a stable and minimal set of generalized IA objects. -- The used IA procedures are made generic to ensure the separation between SA and IA knowledge. We classify them according to their IA objects parameters. (2) domain-specific knowledge: -- control and ordering of such procedures according to scene information are identified and represented in an adequate form to be integrated in the system. The choices made above (theoretical definitions and organization of IA objects and procedures, and the separation between IA and domain-specific knowledge) that ensure generality and application- independence in MII is explained and their validity shown on the selected example. The approach is to be generalized to multimodality medical image interpretation.

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