SEL-Net: a multimodal image segmentation method based on spatial attention mechanism

Ke Xu; Min Li; Yunling Wang; Hongbing Ma

doi:10.1117/12.3005970

10 October 2023 SEL-Net: a multimodal image segmentation method based on spatial attention mechanism

Ke Xu, Min Li, Yunling Wang, Hongbing Ma

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279931 (2023) https://doi.org/10.1117/12.3005970
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Brain segmentation, a crucial research area in medical image processing, plays a vital role in assisting doctors with diagnosing and treating various neurological disorders. The brain consists of multiple tissues and structures, resulting in differential representation across different imaging modalities. This makes it challenging to achieve effective segmentation of image information within a single modality. Therefore, we propose the multimodal brain segmentation method Selective Modality Segmentation Network (SEL-Net), which combines information from multiple image modalities and adopts a method based on a spatial attention mechanism that can integrate multi-modal image information, adaptively adjusts the weights of each modality using a spatial attention mechanism, and optimizes it through different loss function ratios. Different loss function ratios can balance the influence of different modalities, thereby improving the performance and robustness of the model. In the BraTs2019 dataset, SEL-Net proves its effectiveness and superiority, and SEL-Net achieves better results in the metrics of Dice coefficient, sensitivity and specificity. This indicates that SEL-Net has great potential in multimodal brain segmentation, which can provide more accurate and reliable results for medical diagnosis and treatment.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ke Xu, Min Li, Yunling Wang, and Hongbing Ma "SEL-Net: a multimodal image segmentation method based on spatial attention mechanism", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279931 (10 October 2023); https://doi.org/10.1117/12.3005970

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KEYWORDS

Image segmentation

Tumors

Feature selection

Brain

Image processing

Brain tissue

Convolution

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