Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques

Matthew F. Y. Kwan; Kie Chung Cheung; Ian R. Gibson

doi:10.1117/12.387755

6 June 2000 Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques

Matthew F. Y. Kwan, Kie Chung Cheung, Ian R. Gibson

Author Affiliations +

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387755
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

A novel approach is presented for fully automated boundary extraction and rectification of bony tissue from planar CT data. The approach extracts and rectifies feature boundary in a hierarchical fashion. It consists of a fuzzy multilevel thresholding operation, followed by a small void cleanup procedure. Then a binary morphological boundary detector is applied to extract the boundary. However, defective boundaries and undesirable artifacts may still be present. Thus two innovative anatomical knowledge based algorithms are used to remove the undesired structures and refine the erroneous boundary. Results of applying the approach on lumbar CT images are presented, with a discussion of the potential for clinical application of the approach.

Citation Download Citation

Matthew F. Y. Kwan, Kie Chung Cheung, and Ian R. Gibson "Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387755

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