Image processing in the fields of medical diagnosis and therapy follow-up is a challenging issue because of the complexity of the knowledge involved in describing the data and reasoning mechanisms a radiologist uses. A methodological radiologist would be helped if a system could schedule and execute operations and reason on data and user-goals, leaving him with the result interpretation. In this article we show what knowledge is needed to perform the supervision (that is planning and control of execution) of medical image processing programs, and how this knowledge should be described and structured. Our aim is to develop a program supervision tool to help a user in the manipulation of data and programs specific to medical imagery. It must therefore offer a framework to describe knowledge on data, programs and reasoning processes, as well as planning, execution and control mechanisms adapted to the expert in medical image processing. For this purpose, we have developed a constructive modelisation for data description that enables encapsulating knowledge where it is useful for program supervision and we propose a hybrid planning strategy.
The field of reuse in software engineering is large, and a great diversity of approaches claim to be based on a reuse technology. Despite the great diversity of approaches, some general ideas can be identified that all the approaches have in common. These mainly concern the representation of the components and the data that is manipulated by the components. In this paper we identify and analyse a consensus in the literature concerning how to model software components for reuse. We define the basic structures for the components, the data that is being manipulated by the components, and how the components should be reused. These structures are used as a basic model for program supervision, in which programs in software libraries are used as reusable software components. We also identify some areas that are not covered by the existing literature.
In this article we take the first steps towards a functional specification of reusing predefined software components. We do this by presenting a case study: a description of the knowledge contained in OCAPI, using the KADS expertise model. OCAPI is a system that implements knowledge about how to plan and control the execution of a specific kind of software components, namely image processing programs. The KADS expertise model allows to specify this problem solving behaviour in an implementation independent way, and to give a categorization of the knowledge required to generate this behaviour (i.e. functional specification). Based on this case study we will evaluate the structure and contents of the knowledge, and so identify reusable parts and less developed knowledge structures. This will serve as a basis for abstracting from the OCAPI domain (image processing), to a functional specification of reusing predefined software components in general.
This paper deals with the supervision of perception tasks, as component of an autonomous system. First, the role of this component in an autonomous system is presented. Secondly, a model of supervision of perception tasks is proposed: needed control mechanisms as well as knowledge modeling are detailed. Then, an implementation of this model, designed as an expert system shell, named OCAPI, is presented. The facilities provided by OCAPI are shown, through an example: the supervision of an object detection process in road scenes. More precisely, the expert system, developed with OCAPI, automates planning (selection of a sequence of programs) and control of execution (parameter initialization and adjustment, as well as result evaluation). The contents of the knowledge base and a particular utilization of this knowledge base are described.