2022
DOI: 10.1155/2022/5112867
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Lung Nodule Segmentation and Recognition Algorithm Based on Multiposition U-Net

Abstract: Lung nodules are the main lesions of the lung, and conditions of the lung can be directly displayed through CT images. Due to the limited pixel number of lung nodules in the lung, doctors have the risk of missed detection and false detection in the detection process. In order to reduce doctors’ work intensity and assist doctors to make accurate diagnosis, a lung nodule segmentation and recognition algorithm is proposed by simulating doctors’ diagnosis process with computer intelligent methods. Firstly, the att… Show more

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Cited by 6 publications
(5 citation statements)
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“…Lung cancer is the leading cause of mortality in the world [1], affecting both men and women equally. According to the American Cancer Society, 222,500 [2] new instances of lung cancer were diagnosed in 2020 and 155,870 individuals died as a result of the disease. The survival rate for colon cancer is 65.4%, whereas breast cancer has a survival rate of 90.35% and prostate cancer has a survival rate of 99.6% which is much lower than the overall survival rate of 65.4% [3].…”
Section: Introductionmentioning
confidence: 99%
“…Lung cancer is the leading cause of mortality in the world [1], affecting both men and women equally. According to the American Cancer Society, 222,500 [2] new instances of lung cancer were diagnosed in 2020 and 155,870 individuals died as a result of the disease. The survival rate for colon cancer is 65.4%, whereas breast cancer has a survival rate of 90.35% and prostate cancer has a survival rate of 99.6% which is much lower than the overall survival rate of 65.4% [3].…”
Section: Introductionmentioning
confidence: 99%
“…Deep learning utilizes neural networks to train huge amounts of information, effectively International Journal of Intelligent Engineering and Systems, Vol. 16 learn the nodule features in lower grades and form higher-grade features to segment and predict the medical images [13]. The contribution of this proposed paper is specified as follows:…”
Section: Introductionmentioning
confidence: 99%
“…The major contributions of Zhang et al [ 10 ] focused on three parts, i.e., lung parenchyma segmentation, extraction of lung nodule regions, and sign classification based on CT image morphological features. The U-shape network (U-Net) paradigm was utilized to accomplish these three tasks.…”
Section: Introductionmentioning
confidence: 99%
“…The U-shape network (U-Net) paradigm was utilized to accomplish these three tasks. In the lung parenchyma segmentation procedure, the attention mechanism was applied to prevent the background pixel interferences and ameliorate the semantic segmentation accuracy of the U-Net [ 10 ]. Then, the regions of interest can be localized from the receptive fields with the dense atrous convolution approach.…”
Section: Introductionmentioning
confidence: 99%
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