کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6921387 | 864445 | 2015 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Classification of breast regions as mass and non-mass based on digital mammograms using taxonomic indexes and SVM
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Classification of breast regions as mass and non-mass based on digital mammograms using taxonomic indexes and SVM Classification of breast regions as mass and non-mass based on digital mammograms using taxonomic indexes and SVM](/preview/png/6921387.png)
چکیده انگلیسی
Breast cancer is the second most common type of cancer in the world. Several computer-aided detection and diagnosis systems have been used to assist health experts identify suspicious areas that are difficult to perceive with the human eye, thus aiding in the detection and diagnosis of cancer. This work proposes a methodology for the discrimination and classification of regions extracted from mammograms as mass and non-mass. The Digital Database for Screening Mammography (DDSM) was used in this work for the acquisition of mammograms. The taxonomic diversity index (Î) and the taxonomic distinctness (Îâ), which were originally used in ecology, were used to describe the texture of the regions of interest. These indexes were computed based on phylogenetic trees, which were applied to describe the patterns in regions of breast images. Two approaches were used for the analysis of texture: internal and external masks. A support vector machine was used to classify the regions as mass and non-mass. The proposed methodology successfully classified the masses and non-masses, with an average accuracy of 98.88%.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 57, 1 February 2015, Pages 42-53
Journal: Computers in Biology and Medicine - Volume 57, 1 February 2015, Pages 42-53
نویسندگان
Fernando Soares Sérvulo de Oliveira, Antonio Oseas de Carvalho Filho, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Marcelo Gattass,