Image Based Classification Platform: Application to Breast Cancer Diagnosis

View Sample PDF

Author(s): Paolo J. S. Gonçalves (Polytechnic Institute of Castelo Branco, Portugal & Technical University of Lisbon, Portugal), Rui J. Almeida (Erasmus University Rotterdam, The Netherlands), João R. Caldas Pinto (Technical University of Lisbon, Portugal), Susana M. Vieira (Technical University of Lisbon, Portugal)and João M. C. Sousa (Technical University of Lisbon, Portugal)
Copyright: 2013
Pages: 19
Source title: Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care
Source Author(s)/Editor(s): Maria Manuela Cruz-Cunha (Polytechnic Institute of Cavado and Ave, Portugal), Isabel Maria Miranda (Municipality of Guimarães, Portugal)and Patricia Gonçalves (School of Technology at the Polytechnic Institute of Cavado and Ave, Portugal)
DOI: 10.4018/978-1-4666-3990-4.ch031

Keywords: Health Information Systems / Medical Information Science Reference / Medicine & Healthcare

Purchase

View Image Based Classification Platform: Application to Breast Cancer Diagnosis on the publisher's website for pricing and purchasing information.

Abstract

The high number of exams that is done in healthcare institutions increases the medical doctors’ workload, leading to poor working conditions and the increase of wrong diagnoses. As consequence, an automatic system that can help medical doctors in diagnostic tasks is of major interest to any healthcare institution. The chapter proposes an Image Based Classification Platform suitable to help Medical Doctors diagnosing breast cancer, based on mammograms, i.e., to detect if a tumor is present in the image. The platform is twofold, i.e., in the first part the image descriptors are extracted from the image using image-processing algorithms. The obtained descriptors are used in the second part. The second part is related to classification, where computational intelligence methods are used to classify a given image, based on the descriptors obtained in the first phase. Texture analysis based on co-occurrence matrices are applied to obtain the descriptors from the MIAS database of mammograms. From these descriptors, fuzzy models, neural networks, and support vector machines are successfully used to classify the mammograms and obtain a diagnosis.

The IRMA Community

Research IRM

Image Based Classification Platform: Application to Breast Cancer Diagnosis

Purchase

Abstract

Related Content

IRMA Sponsors