AIM: attentionally based interaction model for the interpretation of vascular angiography

Abstract

We propose a model to interpret neurovascular X-ray angiogram (XRA) images interactively. This attentionally based interactive model (AIM) exploits human interaction as part of the solution. AIM posits two channels of interaction: context ("what to look for") and focus-of-attention ("where to look") as the locus of spatial information exchange between the user and the machine. In an AIM system, the user specifies a context (e.g., a carotid vessel) and directs the attentional spotlight to focus machine processing. AIM involves the user with the computer as integral partners and facilitates varying degrees of human intervention in the process. A hierarchy of context abstractions permits the system to function more autonomously (doing high-level tasks like extracting an arterial vessel) in routine interpretation and to require more user intervention (e.g., locating arterial wall boundaries) as the image complexity increases. This is especially important in medical imaging where the medical professional must have ultimate control and confidence in the system. Such technology can have a significant impact on the design of radiological systems.