Incremental System Engineering Using Process Networks
Engineering of complex intelligent systems often requires experts to decompose the task into smaller constituent processes. This allows the domain experts to identify and solve specific sub-tasks, which collectively solve the system’s goals. The engineering of individual processes and their relationships represent a knowledge acquisition challenge, which is complicated by incremental ad-hoc revisions that are inevitable in light of evolving data and expertise. Incremental revisions introduce a risk of degrading the system and limit experts’ ability to build complex intelligent systems. We present an incremental engineering method called ProcessNet that structures incremental ad-hoc changes to a system and mitigates the risks of the changes degrading the system. A medical image analysis application developed using ProcessNet demonstrates that despite a large number of ad-hoc, incremental changes the system’s ability and accuracy in segmenting multiple anatomical regions in High Resolution Computed Tomography (HRCT) scans continue to improve.
KeywordsKnowledge Acquisition Incremental Software Engineering Computer Vision Medical Image Analysis
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