Characterization of Temporal bone in CT Images using Texture Analysis
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 133 | Views: 350

Research Paper | Radiological Sciences | Sudan | Volume 6 Issue 8, August 2017 | Popularity: 6.7 / 10


     

Characterization of Temporal bone in CT Images using Texture Analysis

Zuhal Y. A. Hamd, SuhaibAlameen, Caroline Edward Ayad, Mohamed E. M. Gar-Elnabi


Abstract: This study concern to characterize the Temporal bone were definingto Fluid, Mucosal, Sclerotic and Soft tissues density using texture feature extractionand extract classification features from CT images. The texture analysis technique used to find the gray level variation in CT images. analyzing the image with Interactive Data Language IDL software to measure the grey level variation of images. The results show that texture analysis give classification accuracy of temporal boneto fluid 86.3 %, mucosal 98.2 %, sclerotic 99 %, While the soft tissue density showed a classification accuracy 92.2 %. the overall classification accuracy of temporal bone area 93.6 %. These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate temporal bonearea names.


Keywords: Temporal bone, Chronic Otitis Media, Computed Tomography, Texture Analysis


Edition: Volume 6 Issue 8, August 2017


Pages: 650 - 655



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Zuhal Y. A. Hamd, SuhaibAlameen, Caroline Edward Ayad, Mohamed E. M. Gar-Elnabi, "Characterization of Temporal bone in CT Images using Texture Analysis", International Journal of Science and Research (IJSR), Volume 6 Issue 8, August 2017, pp. 650-655, https://www.ijsr.net/getabstract.php?paperid=25071704, DOI: https://www.doi.org/10.21275/25071704

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