Noelperez

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  • Topic: Mammography, Scientific method, Artificial neural network
  • Pages : 7 (2220 words )
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  • Published : January 4, 2013
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Research Methodology: An example in a Real Project
Noel Pérez
Laboratory of Optics and Experimental Mechanics, Instituto de Engenharia Mecânica e Gestão Industrial. nperez@inegi.up.pt

Abstract. The research methodology defines what the activity of research is, how to proceed, how to measure progress, and what constitutes success. It provides us an advancement of wealth of human knowledge, tools of the trade to carry out research, tools to look at things in life objectively; develops a critical and scientific attitude, disciplined thinking to observe objectively (scientific deduction and inductive thinking); skills of research particularly in the ‘age of information’. Also it defines the way in which the data are collected in a research project. In this paper it presents two components of the research methodology from a real project; the theorical design and framework respectively. Keywords: Research methodology, example of research methodology, theorical framework, theorical design.

1 Introduction
The research methodology defines what the activity of research is, how to proceed, how to measure progress, and what constitutes success. It provides us an advancement of wealth of human knowledge, tools of the trade to carry out research, tools to look at things in life objectively; develops a critical and scientific attitude, disciplined thinking to observe objectively (scientific deduction and inductive thinking); skills of research particularly in the ‘age of information’. The research methodology is a science that studying how research is done scientifically. It is the way to systematically solve the research problem by logically adopting various steps. Also it defines the way in which the data are collected in a research project. 1.1 Study case According to the World Health Organization (WHO) breast cancer is the most common cancer suffered by women in the world, which during the last two decades has increased the women mortality in developing countries. Mammography is the best method used for screening; it is a test producing no inconvenience and with small diagnostic doubts of breast cancer since the preclinical phase [1]. The role of screening mammography in the battle against breast cancer is well established;

women with malignancies detected at an early stage have a significantly better prognosis. However, it is also recognized that the diagnostic interpretation of mammograms continues to be challenging for radiologists with a documented 20% false negative rate [2]. The clinical significance of early breast cancer diagnosis and the higher than desired false-negative rate of screening mammography have motivated the development of computer-aided detection/classification (CAD) systems for decision support. These systems typically involve a hierarchical approach, first applying elaborated image preprocessing steps to enhance suspicious structures in the image and then employing morphologic and textural analysis to better classify these structures between true abnormalities and false positives [2-4]. We made a detailed review of techniques for mammographic image analysis and related CAD systems. This review included methods and techniques from different mammography images sources such as conventional screen film mammography and full-field digital mammography [1-3, 5-9] to ultrasound (US), magnetic resonance imaging (MRI), and computed tomography (CT) images [10-13]. Although true clinical impact of CAD systems is often debated, the scientific community continues to work toward improving the diagnostic performance and clinical integration of CAD technology. For this reason, we consider that reliable CAD systems for automated detection/classification of pathological lesions (PL) will be very useful and helpful to supply a valuable “second opinion” to medical personnel. This project is focused to develop novel methods and algorithms to improve the following fields: image contrast enhancing, accurate PL...
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