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AI Approaches for Breast Cancer Diagnosis: A Comprehensive Study

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International Conference on Innovative Computing and Communications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1394))

Abstract

According to the report of the World Health Organization (WHO), the most common and dangerous disease among women is known to be breast cancer. Breast cancer is a life-threatening disease and may cause death of women. Early detection of breast cancer can decrease mortality rate and improve survival rate in women. Various artificial intelligence (AI) approaches have been used by the research community to build computer-aided diagnosis (CAD) systems for early detection of breast cancer. This study presents various breast imaging modalities used for the cancer diagnosis, related work in this domain, various pre-processing techniques to improve the quality of breast images and applications of machine learning (ML) for breast imaging. The study also presents various deep learning (DL) approaches to build a system for automated breast cancer diagnosis. Various pre-trained deep learning models are also presented in the study. Due to an imbalanced and inconsistent dataset, AI models may not perform well. We have also discussed various techniques to improve the performance of the model. Prediction, segmentation, and classification deep neural network models along with the various imaging modalities are presented which are beneficial for the diagnosis process of breast cancer.

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Authors and Affiliations

  1. Nirma University, Ahmedabad, India

    Harsh Jigneshkumar Patel, Parita Oza & Smita Agrawal

Authors
  1. Harsh Jigneshkumar Patel
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  2. Parita Oza
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  3. Smita Agrawal
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Corresponding author

Correspondence to Harsh Jigneshkumar Patel .

Editor information

Editors and Affiliations

  1. Maharaja Agrasen Institute of Technology, Delhi, India

    Ashish Khanna

  2. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  3. Rajnagar Mahavidyalaya, Birbhum, India

    Siddhartha Bhattacharyya

  4. Computer and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  5. Department of Computer Science, Shaheed Sukhdev College of Business Studies, Rohini, Delhi, India

    Sameer Anand

  6. Department of Computer Science, Shaheed Sukhdev College of Business Studies, Rohini, Delhi, India

    Ajay Jaiswal

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Patel, H.J., Oza, P., Agrawal, S. (2022). AI Approaches for Breast Cancer Diagnosis: A Comprehensive Study. In: Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1394. Springer, Singapore. https://doi.org/10.1007/978-981-16-3071-2_33

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