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pro vyhledávání: '"Santos, Wellington P."'
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Akademický článek
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Publikováno v:
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, v. 5, p. 1-19, 2017
Breast cancer is already one of the most common form of cancer worldwide. Mammography image analysis is still the most effective diagnostic method to promote the early detection of breast cancer. Accurately segmenting tumors in digital mammography im
Externí odkaz:
http://arxiv.org/abs/1712.07312
Autor:
de Lima, Sidney Marlon Lopes, Filho, Abel Guilhermino da Silva, Santos, Wellington Pinheiro dos
Publikováno v:
Computer Methods and Programs in Biomedicine, 134 (2016), 11-29
According to the World Health Organization, breast cancer is the main cause of cancer death among adult women in the world. Although breast cancer occurs indiscriminately in countries with several degrees of social and economic development, among dev
Externí odkaz:
http://arxiv.org/abs/1712.07116
Autor:
Barbosa, Valter Augusto de Freitas, Ribeiro, Reiga Ramalho, Feitosa, Allan Rivalles Souza, da Silva, Victor Luiz Bezerra Araújo, Rocha, Arthur Diego Dias, de Freitas, Rafaela Covello, de Souza, Ricardo Emmanuel, Santos, Wellington Pinheiro dos
Publikováno v:
International Journal of Swarm Intelligence Research, Volume 8, Issue 2, 2017
Electrical Impedance Tomography (EIT) is a noninvasive imaging technique that does not use ionizing radiation, with application both in environmental sciences and in health. Image reconstruction is performed by solving an inverse problem and ill-pose
Externí odkaz:
http://arxiv.org/abs/1712.00789
Alzheimer's disease is the most common cause of dementia, yet hard to diagnose precisely without invasive techniques, particularly at the onset of the disease. This work approaches image analysis and classification of synthetic multispectral images c
Externí odkaz:
http://arxiv.org/abs/1712.00712
Publikováno v:
Learning and Nonlinear Models, v. 8, p. 202-215, 2010
The importance of organizing medical images according to their nature, application and relevance is increasing. Furhermore, a previous selection of medical images can be useful to accelerate the task of analysis by pathologists. Herein this work we p
Externí odkaz:
http://arxiv.org/abs/1712.01695
Publikováno v:
Learning and Nonlinear Models, v. 8, p. 174-201, 2010
The unsupervised classification has a very important role in the analysis of multispectral images, given its ability to assist the extraction of a priori knowledge of images. Algorithms like k-means and fuzzy c-means has long been used in this task.
Externí odkaz:
http://arxiv.org/abs/1712.01696
Autor:
Santos, Wellington Pinheiro dos, de Souza, Ricardo Emmanuel, Silva, Ascendino Flávio Dias e, Filho, Plínio Batista dos Santos
Publikováno v:
Learning and Nonlinear Models, v. 4, p. 43-53, 2008
Alzheimer's disease is the most common cause of dementia, yet difficult to accurately diagnose without the use of invasive techniques, particularly at the beginning of the disease. This work addresses the classification and analysis of multispectral
Externí odkaz:
http://arxiv.org/abs/1712.01700
Autor:
Santos, Wellington Pinheiro dos, de Assis, Francisco Marcos, de Souza, Ricardo Emmanuel, Filho, Plínio Batista dos Santos, Neto, Fernando Buarque de Lima
Publikováno v:
Computerized Medical Imaging and Graphics, v. 33, p. 442-460, 2009
Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. A considerable number of current methods of analysis are based on parametric statistics. Al
Externí odkaz:
http://arxiv.org/abs/1712.01697