A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection Using Breast Thermograms

  • Usha Rani Gogoi
  • Mrinal Kanti Bhowmik
  • Debotosh Bhattacharjee
  • Anjan Kumar Ghosh
  • Gautam Majumdar
Part of the Studies in Computational Intelligence book series (SCI, volume 611)


The growing incidence and mortality rate of breast cancer draw the attention of the researchers to develop a technique for improving the survival rate of the cancer patients. Medical infrared thermography (MIT) with sensitivity 90 % has proved itself as a safe and promising method for early breast cancer detection. Moreover, an abnormal breast thermogram can signify breast pathology. The accurate classification and diagnosis of these breast thermograms is one of the major problem in decision making for treatments, which leads to the utilization of hybrid intelligent system in breast thermogram classification. Hybrid intelligent system plays a vital role in survival prediction of a breast cancer patient, and it is highly significant in decision making for treatments and medications. The primary objective of a hybrid intelligent system is to take the advantages of its constituent models and at the same time lessen their limitations. This chapter is an attempt to highlight the reliability of infrared breast thermography and hybrid intelligent system in breast cancer detection and diagnosis. A detailed overview of infrared breast thermography including its principles and role in early breast cancer detection is described here. Several research works are carried out by various researchers to identify the breast pathology from breast thermograms by using hybrid intelligent techniques which include extraction and analysis of several statistical features. A study of research works related to feature extraction and classification of breast thermograms using various types of hybrid classifiers is also included in this chapter.


Breast cancer Digital infrared imaging Infrared breast thermography Breast asymmetry Breast cancer detection 



The work presented here is being conducted in the Bio-Medical Infrared Image Processing Laboratory (B-MIRD), Department of Computer Science and Engineering, Tripura University (A Central University), Suryamaninagar-799022, Tripura(W). The research work is supported by the Grant No. BT/533/NE/TBP/2013, Dated 03/03/2014 from the Department of Biotechnology (DBT), Government of India. The first author would like to thank Prof. Barin Kumar De, Department of Physics, Tripura University (A Central University) for his kind support to carry out this work. The second author also would like to thank Prof. Siddhartha Majumder, Advisor, Medical Education, Government of Tripura for his valuable advices to carry out this project.


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Copyright information

© Springer India 2016

Authors and Affiliations

  • Usha Rani Gogoi
    • 1
  • Mrinal Kanti Bhowmik
    • 1
  • Debotosh Bhattacharjee
    • 2
  • Anjan Kumar Ghosh
    • 1
  • Gautam Majumdar
    • 3
  1. 1.Department of Computer Science and EngineeringTripura University (A Central University)TripuraIndia
  2. 2.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia
  3. 3.Radiotherapy Department, Regional Cancer CenterAgartala Government Medical College AgartalaTripuraIndia

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