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A Comprehensive Study on Pre-trained Models for Skin Lesion Diagnosis in a Federated Setting

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Computer Vision and Image Processing (CVIP 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2011))

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Abstract

Privacy has been one of the main concerns when it comes to the application of deep learning in the medical domain. Medical institutes prioritizing the privacy of their patients do not make their data public, making it difficult to build better models to diagnose rare diseases. But, after the advent of federated learning, there have been immense improvements toward building better models that employ patient’s private data without compromising their privacy. In this paper, we comprehensively study multiple models to diagnose skin lesions in a federated setting. Replicating real-life scenarios, we experiment in different settings where the number of clients or hospitals that participate varies. Further, we explore if the pre-trained weights obtained from natural image datasets could assist in building a better model for diagnosing skin lesions.

This work was funded by the Department of Science and Technology (DST) under the Fund for Improvement of S &T Infrastructure (FIST), Govt. of India [Grant no. SR/FST/ET-I/2020/578], and Science and Engineering Research Board (SERB) [Grant no. EEQ/2021/000804].

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Notes

  1. 1.

    https://pytorch.org/vision/stable/models.html.

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Authors and Affiliations

  1. Advanced Signal and Image Processing (ASIP) Lab, Department of Electronics and Communication Engineering, Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram, Chennai, 600127, India

    C. Siddarth, Ajay Kumar Reddy Poreddy & Priyanka Kokil

Authors
  1. C. Siddarth
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  2. Ajay Kumar Reddy Poreddy
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  3. Priyanka Kokil
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Corresponding author

Correspondence to Priyanka Kokil .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology, Jammu, India

    Harkeerat Kaur

  2. Indian Institute of Technology, Jammu, India

    Vinit Jakhetiya

  3. Indian Institute of Technology, Ropar, India

    Puneet Goyal

  4. Indian Institute of Information Technology, Jabalpur, India

    Pritee Khanna

  5. Indian Institute of Technology, Roorkee, Uttarakhand, India

    Balasubramanian Raman

  6. Indian Institute of Technology, Roorkee, Uttarakhand, India

    Sanjeev Kumar

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Siddarth, C., Poreddy, A.K.R., Kokil, P. (2024). A Comprehensive Study on Pre-trained Models for Skin Lesion Diagnosis in a Federated Setting. In: Kaur, H., Jakhetiya, V., Goyal, P., Khanna, P., Raman, B., Kumar, S. (eds) Computer Vision and Image Processing. CVIP 2023. Communications in Computer and Information Science, vol 2011. Springer, Cham. https://doi.org/10.1007/978-3-031-58535-7_40

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  • DOI: https://doi.org/10.1007/978-3-031-58535-7_40

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