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LeukoCapsNet: a resource-efficient modified CapsNet model to identify leukemia from blood smear images

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Abstract

Leukemia is one of the deadly cancers which spreads itself at an exponential rate and has a detrimental impact on leukocytes in the human blood. To automate the process of leukemia detection, researchers have utilized deep learning networks to analyze blood smear images. In our research, we have proposed the usage of networks that mimic the human brain’s real working. These models are fed features from numerous convolution layers, each having its own set of additional skip connections. It is then stored and processed as vectors, making them rotationally invariant as well, a characteristic not found in other deep learning networks, specifically convolutional neural networks (CNNs). The network is then pruned by 20% to make it more deployable in resource-constrained environments. This research also compares the model’s performance by four ablation experiments and concludes that the proposed model is optimal. It has also been tested on three different types of datasets to highlight its robustness. The average values of all three datasets correspond to specificity: 96.97%, sensitivity: 96.81%, precision: 96.79% and accuracy: 97.44%. In a nutshell, the outcomes of the proposed model, i.e., PrunedResCapsNet make it more dynamic and effective compared with other existing methods.

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Availability of data and code

The datasets analyzed during the current study have been taken from two public repositories which are https://scotti.di.unimi.it/all/ and https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=52758223. Code files for the proposed model will be provided upon receiving a reasonable request.

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Acknowledgements

The review paper is supported by University Grants Commission (UGC), New Delhi, India, which provides fellowship to research scholars under the scheme NET-JRF.

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  1. UIET, Panjab University, Chandigarh, India

    Sabrina Dhalla, Ajay Mittal & Savita Gupta

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  1. Sabrina Dhalla
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Correspondence to Ajay Mittal.

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Dhalla, S., Mittal, A. & Gupta, S. LeukoCapsNet: a resource-efficient modified CapsNet model to identify leukemia from blood smear images. Neural Comput & Applic 36, 2507–2524 (2024). https://doi.org/10.1007/s00521-023-09157-w

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