Knowledge Representation Learnt from User Interactions

A novel method of implementing an adaptable characteristic in a knowledge-based component has been suggested by capturing user interactions with a CAD tool.

Fenster and Kender [15] proposed the use of a diagnostic tool for the interpretation of computed tomography (CT) images. The authors utilize a boundary-based segmentation technique termed the live wire paradigm. The motivation for the scheme is based on an attempt to utilize the interaction with an expert clinician during segmentation, thereby learning from the users feedback for use in subsequent segmentations. Under the proposed framework, a 2D boundary is constructed around a ROI based in part on image properties and knowledge acquired in training when manual segmentation is performed. The tool utilizes an optimal feature selection process to determine the best boundary position from the available information.

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