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SU‐E‐E‐16: The Application of Texture Analysis for Differentiation of Central Cancer From Atelectasis
Author(s) -
Gao M,
Fan T,
Duan J
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4923936
Subject(s) - atelectasis , medicine , lung cancer , nuclear medicine , correlation , radiation therapy , radiology , texture (cosmology) , lung , mathematics , pathology , artificial intelligence , image (mathematics) , computer science , geometry
Purpose: Prospectively assess the potential utility of texture analysis for differentiation of central cancer from atelectasis. Methods: 0 consecutive central lung cancer patients who were referred for CT imaging and PET‐CT were enrolled. Radiotherapy doctor delineate the tumor and atelectasis according to the fusion imaging based on CT image and PET‐CT image. The texture parameters (such as energy, correlation, sum average, difference average, difference entropy), were obtained respectively to quantitatively discriminate tumor and atelectasis based on gray level co‐occurrence matrix (GLCM) Results: The texture analysis results showed that the parameters of correlation and sum average had an obviously statistical significance(P<0.05). Conclusion: the results of this study indicate that texture analysis may be useful for the differentiation of central lung cancer and atelectasis.