**Breast Cancer Detection by Means of Artificial Neural Networks** Provisional chapter

DOI: 10.5772/intechopen.71256

Breast Cancer Detection by Means of Artificial Neural

Jose Manuel Ortiz-Rodriguez, Carlos Guerrero-Mendez, Maria del Rosario Martinez-Blanco, Salvador Castro-Tapia, Mireya Moreno-Lucio, Ramon Jaramillo-Martinez, Luis Octavio Solis-Sanchez, Margarita de la Luz Martinez-Fierro, Idalia Garza-Veloz, Jose Cruz Moreira Galvan and Jorge Alberto Barrios Garcia Networks Jose Manuel Ortiz-Rodriguez, Carlos Guerrero-Mendez, Maria del Rosario Martinez-Blanco, Salvador Castro-Tapia, Mireya Moreno-Lucio, Ramon Jaramillo-Martinez, Luis Octavio Solis-Sanchez, Margarita de la Luz Martinez-Fierro, Idalia Garza-Veloz, Jose Cruz Moreira Galvan and Jorge Alberto Barrios Garcia

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.71256

#### Abstract

Breast cancer is a fatal disease causing high mortality in women. Constant efforts are being made for creating more efficient techniques for early and accurate diagnosis. Classical methods require oncologists to examine the breast lesions for detection and classification of various stages of cancer. Such manual attempts are time consuming and inefficient in many cases. Hence, there is a need for efficient methods that diagnoses the cancerous cells without human involvement with high accuracies. In this research, image processing techniques were used to develop imaging biomarkers through mammography analysis and based on artificial intelligence technology aiming to detect breast cancer in early stages to support diagnosis and prioritization of high-risk patients. For automatic classification of breast cancer on mammograms, a generalized regression artificial neural network was trained and tested to separate malignant and benign tumors reaching an accuracy of 95.83%. With the biomarker and trained neural net, a computer-aided diagnosis system is being designed. The results obtained show that generalized regression artificial neural network is a promising and robust system for breast cancer detection. The Laboratorio de Innovacion y Desarrollo Tecnologico en Inteligencia Artificial is seeking collaboration with research groups interested in validating the technology being developed.

Keywords: breast cancer detection, digital image processing, artificial neural networks, biomarkers, computer-aided diagnosis

© 2018 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.
