Extrapolation techniques for textural characterization of tissue in medical images

William F. Sensakovic; Samuel G. Armato III; Adam Starkey

doi:10.1117/12.698383

30 March 2007 Extrapolation techniques for textural characterization of tissue in medical images

William F. Sensakovic, Samuel G. Armato III, Adam Starkey

Proceedings Volume 6514, Medical Imaging 2007: Computer-Aided Diagnosis; 65143G (2007) https://doi.org/10.1117/12.698383
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

The low in-plane resolution of thoracic computed tomography (CT) scans may force texture analysis in regions of interest (ROIs) that are not completely filled by the tissue under analysis. The inclusion of extraneous tissue textures within the ROI may substantially contaminate these texture descriptor values. The goal of this study is to investigate the accuracy of different image extrapolation methods when calculating common texture descriptor values. Three extrapolation methods (mean fill, tiled fill, and CLEAN deconvolution) were applied to 480 lung parenchyma regions of interest (ROIs) extracted from transverse thoracic CT sections. The ROIs were artificially corrupted, and each extrapolation method was independently applied to create extrapolation-corrected ROIs. Texture descriptor values were calculated and compared for the original, corrupted, and extrapolation-corrected ROIs. For 51 of 53 texture descriptors, the values calculated from extrapolation-corrected ROIs were more accurate than values calculated from corrupted ROIs. Further, a "best" extrapolation method for all texture descriptors was not identified, which implies that the choice of extrapolation method depends on the texture descriptors applied in a given tissue classification scheme.

Citation Download Citation

William F. Sensakovic, Samuel G. Armato III, and Adam Starkey "Extrapolation techniques for textural characterization of tissue in medical images", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65143G (30 March 2007); https://doi.org/10.1117/12.698383

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