Biomedical Computing for Breast Cancer Detection and Diagnosis

Biomedical Computing for Breast Cancer Detection and Diagnosis

Wellington Pinheiro dos Santos (Universidade Federal de Pernambuco, Brazil), Washington Wagner Azevedo da Silva (Universidade Federal de Pernambuco, Brazil) and Maira Araujo de Santana (Universidade Federal de Pernambuco, Brazil)
Release Date: July, 2020|Copyright: © 2021 |Pages: 357
DOI: 10.4018/978-1-7998-3456-4
ISBN13: 9781799834564|ISBN10: 1799834565|EISBN13: 9781799834571
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Description & Coverage
Description:

Despite success with treatment when diagnosed early, breast cancer is still one of the most fatal forms of cancer for women. Imaging diagnosis is still one of the most efficient ways to detect early breast changes with mammography among the most used techniques. However, there are other techniques that have emerged as alternatives or even complementary tests in the early detection of breast lesions (e.g., breast thermography and electrical impedance tomography). Artificial intelligence can be used to optimize image diagnosis, increasing the reliability of the reports and supporting professionals who do not have enough knowledge or experience to make good diagnoses.

Biomedical Computing for Breast Cancer Detection and Diagnosis is a collection of research that presents a review of the physiology and anatomy of the breast; the dynamics of breast cancer; principles of pattern recognition, artificial neural networks, and computer graphics; and the breast imaging techniques and computational methods to support and optimize the diagnosis. While highlighting topics including mammograms, thermographic imaging, and intelligent systems, this book is ideally designed for medical oncologists, surgeons, biomedical engineers, medical imaging professionals, cancer researchers, academicians, and students in medicine, biomedicine, biomedical engineering, and computer science.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Artificial Neural Networks
  • Breast Cancer
  • Cancer Diagnosis
  • Electrical Impedance Tomography
  • Image Reconstruction
  • Intelligent Systems
  • Machine Learning
  • Mammary Ultrasound
  • Mammography
  • Medical Imaging
  • Physiology of Mammary Tissue
  • Thermographic Imaging
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Editor Biographies
Wellington Pinheiro dos Santos received a bachelor's degree in Electrical Electronics Engineering (2001) and MSc in Electrical Engineering (2003) from the Federal University of Pernambuco, and Ph.D. in Electrical Engineering from the Federal University of Campina Grande (2009). He is currently a Professor of the Department of Biomedical Engineering at the Federal University of Pernambuco, acting in Undergraduate and Graduate Programs in Biomedical Engineering. He is a member of the Graduate Program in Computer Engineering from the Polytechnic School of Pernambuco, University of Pernambuco, since 2009. He has experience in the area of Computer Science, acting on the following themes: digital image processing, pattern recognition, computer vision, evolutionary computation, numerical methods of optimization, computational intelligence, computer graphics, virtual reality, game design and applications of Computing and Engineering in Medicine and Biology. He is a member of the Brazilian Society of Biomedical Engineering (SBEB), the Brazilian Society of Computational Intelligence, and the International Federation of Medical and Biological Engineering (IFMBE).
Washington Wagner Azevedo da Silva holds a PhD in Computer Science from the Federal University of Pernambuco - UFPE (2017) and a master in Computer Science from the Federal University of Pernambuco - UFPE (2011). He graduated in Systems Analysis at Universidade Salgado de Oliveira - UNIVERSO (2004). He did a post-doctorate at the Department of Biomedical Engineering at the Federal University of Pernambuco - UFPE (10/2017 to 10/2019) with Prof. Dr. Wellington Pinheiro dos Santos. He was a Test Engineer for the CIn / Motorola project (in the period from 10/05/2006 to 10/31/2007). He has experience in Computer Science, acting on the following subjects: Software Test Engineering, Artificial Intelligence, Artificial Neural Networks, Hybrid Intelligent Systems, Handwriting Recognition, pattern recognition and Biomedical Engineering.
Maira Araujo de Santana has a Master's degree in Biomedical Engineering at the Federal University of Pernambuco (UFPE) and member of the Biomedical Computing Research Group. She holds a degree in Biomedical Engineering from the Federal University of Pernambuco (2017). She has fluency in Portuguese (native language) and English, as well as basic knowledge of Spanish and German. She completed an internship in Clinical Engineering at Hospital das Clínicas de Pernambuco (09/2016 - 01/2017). She was a Scholarship for Science for Borders Program of the Federal Government / CAPES in the United States for one year (edict 180: 08/2015 - 08/2016), of which nine months (08/2015 - 05/2016) were dedicated to She has a BA in Biomedical Engineering at the University of Alabama at Birmingham (UAB), AL (USA) and in the last three months (05/2016 - 08/2016) she worked as a researcher at the Carl E Ravin Advanced Imaging Laboratories (RAILabs) - Duke University, NC, USA - deepening specific knowledge of the area of image processing (sub-area of Biomedical Engineering) and acquiring experience in laboratory stage, scientific production, programming in MATLAB language and Office package.
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