25 April 1997 New approach in knowledge-based automatic interpretation of CT skull images
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Abstract
In this paper we present an automatic system for the segmentation and recognition of different tissues in maxillofacial CT images. The system is designed as a low level segmentation (LLS) module and a brain module performing high level segmentation (HLS) to dynamically validate anatomic information of these structures. Our procedure differs from previous attempts in its use of advanced low level segmentation operators and specific knowledge bases that embody knowledge about tissue characteristics, and not about specific anatomical structures or organs. In order to augment the confidence and accuracy in segmentation of teeth and implants, which are very similar to adjacent cortical(and espongiosa-) tissues, a spatial matched filter approach is applied, which allows a shape sensitive target detection and initial approximation of trained object forms. System results tested on CT images from five patients running on a PC based hardware are very promising both in accuracy and processing time. The developed system has applications in dental implantology, allowing the optimisation of surgery 3D planning in low cost PC-based workstations. Keywords: expert systems, image segmentation, maxillofacial surgery planning, spatial matched filters
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Vincente Grau Colomer, Mariano Luis Alcaniz-Raya, Christian Juan Knoll, Salvador Estela Albalat, M. Carmen Juan, "New approach in knowledge-based automatic interpretation of CT skull images", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274162; https://doi.org/10.1117/12.274162
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