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A Drive Through Computer-Aided Diagnosis of Breast Cancer: A Comprehensive Study of Clinical and Technical Aspects

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Recent Innovations in Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 832))

Abstract

Breast cancer is a very common and life-threatening disease in women worldwide. The number of breast cancer cases is increasing with time. Prevention of this disease is very challenging and still remains a question at large, but if detected in advance, the survival rate can be increased. The advances in deep learning have demonstrated a lot of changes in the development of Computer-Aided Diagnosis (CAD) of breast cancer. With the noteworthy progress of the new development of artificial intelligence which is deep neural networks, the diagnostic potentialities of deep learning methods are closely approaching the expertise of a human. Although deep learning has substantial improvements and advancements, especially Convolutional Neural Networks (CNN), there are still some challenges that are required to be addressed to build an effective CAD system that can serve as a “second opinion” tool for practitioners. A comprehensive review of clinical aspects of breast cancer like risk factors, breast abnormalities, and BIRADS (Breast Imaging Reporting and Data System) is presented in the paper. This paper also presents CAD systems that are recently developed for breast cancer segmentation, detection, and classification. An overview of mammography datasets used in literature and challenges in applying CNN for medical images are also discussed in the paper.

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Authors and Affiliations

  1. Pandit Deendayal Energy University, Gandhinagar, India

    Parita Oza, Paawan Sharma & Samir Patel

Authors
  1. Parita Oza
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  2. Paawan Sharma
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  3. Samir Patel
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Corresponding author

Correspondence to Parita Oza .

Editor information

Editors and Affiliations

  1. KIET Group of Institutions, Ghaziabad, India

    Pradeep Kumar Singh

  2. Department of CSE, Central University of Jammu, Jammu and Kashmir, India

    Yashwant Singh

  3. Department of Electrical Engineering, IIT Patna, Patna, India

    Maheshkumar H. Kolekar

  4. Department of Management Studies and School of Artificial Intelligence, Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Arpan Kumar Kar

  5. School of Technology, Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal

    Paulo J. S. Gonçalves

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Oza, P., Sharma, P., Patel, S. (2022). A Drive Through Computer-Aided Diagnosis of Breast Cancer: A Comprehensive Study of Clinical and Technical Aspects. In: Singh, P.K., Singh, Y., Kolekar, M.H., Kar, A.K., Gonçalves, P.J.S. (eds) Recent Innovations in Computing. Lecture Notes in Electrical Engineering, vol 832. Springer, Singapore. https://doi.org/10.1007/978-981-16-8248-3_19

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