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February 12, 2024IEEE/CAA Journal of Automatica Sinica48 citationsOpen Access

Dendritic Deep Learning for Medical Segmentation

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ZLZhipeng LiuZZZhiming ZhangZLZhenyu Lei

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Abstract

Dear Editor, This letter presents a novel segmentation approach that leverages dendritic neurons to tackle the challenges of medical imaging segmentation. In this study, we enhance the segmentation accuracy based on a SegNet variant including an encoder-decoder structure, an upsampling index, and a deep supervision method. Furthermore, we introduce a dendritic neuron-based convolutional block to enable nonlinear feature mapping, thereby further improving the effectiveness of our approach. The proposed method is evaluated on medical imaging segmentation datasets, and the experimental results demonstrate that it is superior to state-of-the-art methods in terms of performance.

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Cite This Study

Liu et al. (2024) studied this question.

synapsesocial.com/papers/68e796dbb6db643587707b97https://doi.org/10.1109/jas.2023.123813
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