Method of differentiation of benign and malignant masses in digital mammograms using texture analysis based on phylogenetic diversity

Author:

Carvalho Edson Damasceno,de Carvalho Filho Antonio Oseas,de Sousa Alcilene Dalília,Silva Aristófanes Corrêa,Gattass Marcelo

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science,Control and Systems Engineering

Reference29 articles.

1. A review of computer-aided detection and diagnosis of breast cancer in digital mammography;Mina;J Med Sci,2015

2. A mass classification using spatial diversity approaches in mammography images for false positive reduction;Junior;Expert Syst Appl,2013

3. Computer-aided diagnosis of breast lesions in medical images;Giger;Comput Sci Eng,2000

4. Benign and malignant breast tumors classification based on region growing and cnn segmentation;Rouhi;Expert Syst Appl,2015

5. Novel technique for the detection of abnormalities in mammograms using texture and geometric features;Paramkusham,2015

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