Breast tumor classification in ultrasound images using support vector machines and neural networks-Reference-Cited by-同舟云学术

Breast tumor classification in ultrasound images using support vector machines and neural networks

Published:2016-10-10 Issue:3 Volume:32 Page:283-292
ISSN:2446-4740
Container-title:Research on Biomedical Engineering
language:
Short-container-title:Res. Biomed. Eng.

Author:

Nascimento Carmina Dessana Lima¹,Silva Sérgio Deodoro de Souza¹,Silva Thales Araújo da¹,Pereira Wagner Coelho de Albuquerque²,Costa Marly Guimarães Fernandes¹,Costa Filho Cicero Ferreira Fernandes¹

Affiliation:

1. Universidade Federal do Amazonas, Brazil

2. Universidade Federal do Rio de Janeiro, Brazil

Publisher

FapUNIFESP (SciELO)

Subject

Biomedical Engineering

Link

http://www.scielo.br/pdf/reng/v32n3/2446-4740-reng-2446-474004915.pdf

Reference37 articles.

1. Complexity curve and grey level co-occurrence matrix in the texture evaluation of breast tumor on ultrasound images;Alvarenga AV;Medical Physics,2007

2. Assessing the performance of morphological parameters in distinguishing breast tumors on ultrasound images;Alvarenga AV;Medical Engineering & Physics,2010

3. Assessing the combined performance of texture and morphological parameters in distinguishing breast tumors in ultrasound images;Alvarenga AV;Medical Physics,2012

4. Improvement in breast tumor discrimination by support vector machines and speckle-emphasis texture analysis;Chang RF;Ultrasound in Medicine & Biology,2003

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