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M-AResNet: a novel multi-scale attention residual network for melting curve image classification

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Abstract

Melting curve image is a hallmark of quantitative polymerase chain reaction and is a crucial indicator for the validity of the cycle threshold. Current mainstream methods concentrate on analyzing the melting curve images via artificial process. Therefore, we design a novel multi-scale attention residual network, leveraging various levels space features for accurately classifying the melting curve images. Two modular components are designed in our algorithm. A multi-scale feature extraction module that consists of multi-parallel attention resnet units to selectively capture close related information from various scale feature maps while a series of adaptive multi-scale fusion modules to complete cross-subnet fusion of information. In addition, we also collect massive fluorescence signal data to draw melting curve images for constructing a novel dataset. Our method is evaluated on 3 different benchmark datasets including the self-constructed melting curve image dataset, heartbeat signal dataset and natural color image dataset, a significant highlight is that it achieves a 2.0% accuracy improvement over state-of-the-art in average.

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Data Availability

The datasets analysed during the current study are available from the corresponding author on reasonable request.

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Funding

This research is supported by the National Natural Science Foundation of China (61876070).

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Authors and Affiliations

  1. School of Software, Nanchang University, Nanjingdong Street, Nanchang, 33000, Jiangxi, China

    Pengxiang Su

  2. College of Computer Science and Technology, Jilin University, Qianjin Street, Changchun, 130000, Jilin, China

    Pengxiang Su, Xuanjing Shen, Haipeng Chen & Yu Liu

  3. School of Mathematics and Computer Sciences, Nanchang University, Xuefu Street, Nanchang, 33000, Jiangxi, China

    Di Gai

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  1. Pengxiang Su
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Correspondence to Haipeng Chen.

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Su, P., Shen, X., Chen, H. et al. M-AResNet: a novel multi-scale attention residual network for melting curve image classification. Multimed Tools Appl 82, 42961–42976 (2023). https://doi.org/10.1007/s11042-023-14694-6

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