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Improved CAPSNET model with modified loss function for medical image classification

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Abstract

A capsule network (CapsNet) is a new neural network model that is recently evolving in the field of image classification. Some of the shortcomings of traditional convolutional neural networks (CNNs) are compensated by the characteristics of CapsNet. It has proven to be effective at a variety of tasks, predominantly in medical image recognition with activation capsules. In this paper, image classification using the special designs in CapsNet is examined in depth. An additional reconstruction loss is used in the proposed work to empower the steering capsules and encode the input’s instantiation parameters. The active vectors of higher-level capsules are used for the classification mechanism. The calculation at that point remakes the input picture thus utilizing these active vectors. The directing capsule’s yield is sent into a decoder with three completely associated layers, which limits the whole of squared disparities between the calculated unit yields and the pixel power. In comparison to a typical CapsNet, the improved CapsNet method incorporates the extra parameters such as the number of measurements in each capsule sort (essential or directing capsules), the number of essential and directing capsules, and the number of channels within the capsule layer that are used for image classification. The experimental results show promising results in image recognition when compared to other CNN model-based algorithms.

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Authors and Affiliations

  1. Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, Erode, Tamilnadu, India

    J. Deepika

  2. Department of Information Technology, K S Rangasamy College of Technology, Tiruchengode, Namakkal, Tamilnadu, India

    C. Rajan

  3. Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, Tamilnadu, India

    T. Senthil

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  1. J. Deepika
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  2. C. Rajan
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  3. T. Senthil
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Correspondence to J. Deepika.

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Deepika, J., Rajan, C. & Senthil, T. Improved CAPSNET model with modified loss function for medical image classification. SIViP 16, 2269–2277 (2022). https://doi.org/10.1007/s11760-022-02192-5

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  • DOI: https://doi.org/10.1007/s11760-022-02192-5

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