Parallel Deep Learning Algorithms With Hybrid Attention Mechanism for Image Segmentation of Lung Tumors

At present, medical images have played a more and more important role in clinical treatment. Lung images provide an important reference for doctors to make a diagnosis. Especially for surgical patients, a tumor can be accurately removed based on the full cognition about its size, position, and quant...

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Bibliographic Details
Published inIEEE transactions on industrial informatics Vol. 17; no. 4; pp. 2880 - 2889
Main Authors Hu, Hexuan, Li, Qingqiu, Zhao, Yunfeng, Zhang, Ye
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.04.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Cancer
Cognition
Computed tomography
Convolution
Deep learning
Diagnosis
Health services
Hybrid attention mechanism
Image segmentation
Lung
lung images
Lungs
Machine learning
Medical imaging
parallel deep learning algorithm
Physicians
Tumors
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Summary:At present, medical images have played a more and more important role in clinical treatment. Lung images provide an important reference for doctors to make a diagnosis. Especially for surgical patients, a tumor can be accurately removed based on the full cognition about its size, position, and quantity. Therefore, computer-aided diagnosis for the analysis and treatment of a lot of lung tumor images is very important. Aiming at complexity and self-adaption of image segmentation in lung tumors, this article proposed a parallel deep learning algorithm with hybrid attention mechanism for image segmentation. First, lung parenchyma was extracted via preprocessing images. Then, images were input into hybrid attention mechanism and densely connected convolutional networks (DenseNet) module, respectively, where hybrid attention mechanism consisted of a spatial attention mechanism and a channel attention mechanism. Finally, four feasible solutions were proposed for the verification through changing the convolution quantity of dense block in DenseNet. The network structure with the better performance was achieved. The experimental results prove the parallel deep learning algorithm with hybrid attention mechanism performed well in image segmentation of lung tumors, and its accuracy can reach 94.61%.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2020.3022912