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: 161 | Views: 348

Research Paper | Medicine Science | Sudan | Volume 6 Issue 2, February 2017 | Popularity: 6.7 / 10


     

Characterization of Breast Fibroadenoma in U/S Images Using Image Texture Analysis Techniques

Amal mammon, Mohammed Elfadil, A. H. A. Bakry


Abstract: A new approach to texture characterization from breast ultrasound scan is presented. This study was aimed to use the texture analysis and classification methods to characterize the breast Fibroadenoma, cyst and normal breast regions in U/S images using image processing program (IDL, interactive data language). An analytical case control study of Breast US images of 130 adult subjects with Fibroadenoma, cyst and normal images that in which used as entry data. Tiff format was created as IDL variables and then using 3x3 window the image was scanned and based on the image histogram the selected feature also called FOS was calculated using this window. Linear discriminant analysis was used for the tissue classification. The study found that the Fibroadenoma texture reveal a different underlying pattern compared to the cyst and normal breast tissues with classification sensitivity and specificity 100 % and 92.5 % respectively for fibroadenoma, and the combination of the texture features throughout the different U/S image phases provide the highest predictive overall accuracy of 95 % using linear discriminant analysis technique.


Keywords: Fibroadenoma, Breast Ultrasound, Breast Cyst, Tumor


Edition: Volume 6 Issue 2, February 2017


Pages: 818 - 821



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Amal mammon, Mohammed Elfadil, A. H. A. Bakry, "Characterization of Breast Fibroadenoma in U/S Images Using Image Texture Analysis Techniques", International Journal of Science and Research (IJSR), Volume 6 Issue 2, February 2017, pp. 818-821, URL: https://www.ijsr.net/getabstract.php?paperid=ART2017525, DOI: https://www.doi.org/10.21275/ART2017525



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