Mammographic mass classification using filter response patches

Autor:	Zobia Suhail, Azam Hamidinekoo, Reyer Zwiggelaar
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	receiver operating characteristic curve naive Bayes classifier Digital Database-for-Screening Mammography database texton dictionary generation filter bank responses texture-based mass classification Computer applications to medicine. Medical informatics R858-859.7 Computer software QA76.75-76.765
Zdroj:	IET Computer Vision, Vol 12, Iss 8, Pp 1060-1066 (2018)
Druh dokumentu:	article
ISSN:	1751-9640 1751-9632
DOI:	10.1049/iet-cvi.2018.5244
Popis:	Considering the importance of early diagnosis of breast cancer, a supervised patch‐wise texton‐based approach has been developed for the classification of mass abnormalities in mammograms. The proposed method is based on texture‐based classification of masses in mammograms and does not require segmentation of the mass region. In this approach, patches from filter bank responses are utilised for generating the texton dictionary. The methodology is evaluated on the publicly available Digital Database for Screening Mammography database. Using a naive Bayes classifier, a classification accuracy of 83% with an area under the receiver operating characteristic curve of 0.89 was obtained. Experimental results demonstrated that the patch‐wise texton‐based approach in conjunction with the naive Bayes classifier constructs an efficient and alternative approach for automatic mammographic mass classification.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/4d838b892fd14064b335ee6f12296bf1 Zobrazit plný text záznamu Plný text View record in DOAJ