Dual-source computed tomography image information under deep learning algorithm in evaluation of coronary artery lesion in children with Kawasaki disease

Luo, Ping; Li, Jinling

doi:10.1007/s11227-021-04077-9

Cited by 2 publications

(2 citation statements)

References 20 publications

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“…Ramot et al put forward a network pruning strategy [ 22 ], which starts with pre-training the model, then replaces the parameters below a certain threshold with zeros to form a sparse matrix, and finally trains the sparse CNN. Luo and Li put forward a classic CNN framework, which shows a significant improvement in image classification tasks compared with previous methods [ 23 ]. The overall architecture of their method, namely, AlexNet, is similar to LeNet-5 but has a deeper structure.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning

Jiang

2022

Journal of Environmental and Public Health

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In social science and natural science, MP (Marxist Philosophy) has played an active role in promoting its development, and MP also guides people’s practice and understanding. There is an inevitable connection with system theory MP. In a sense, both system theory and PMbelong to methodology and both contain the viewpoints of movement and development. In this paper, various text features in natural scenes are discussed in detail, and the original vector is studied by using CNN (Convective Neural Network) of DL (Deep Learning), so as to construct a one-dimensional text vector and realize the mutual influence and continuous optimization of feature extraction and text clustering. The experimental results show that under the condition of calculating the current cosine similarity measure, the accuracy rate is the highest, reaching 93.67%. This algorithm can effectively improve its performance in text classification tasks on large data sets.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning

Jiang

2022

Journal of Environmental and Public Health

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“…Convolutional neural networks (CNNs) are utilized in image segmentation, classification, and target positioning [ 9 ]. Reducing the size of the convolution kernel can faster the running speed of CNN [ 10 ]. The CNN was optimized in the study.…”

Section: Introductionmentioning

confidence: 99%

Optimized Deconvolutional Algorithm‐based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction

Chen

Bai

Shu

et al. 2022

Contrast Media & Molecular Imaging

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To apply deconvolution algorithm in computer tomography (CT) perfusion imaging of acute cerebral infarction (ACI), a convolutional neural network (CNN) algorithm was optimized first. RIU-Net was applied to segment CT image, and then equipped with SE module to enhance the feature extraction ability. Next, the BM3D algorithm, Dn CNN, and Cascaded CNN were compared for denoising effects. 80 patients with ACI were recruited and grouped for a retrospective analysis. The control group utilized the ordinary method, and the observation group utilized the algorithm proposed. The optimized model was utilized to extract the feature information of the patient’s CT images. The results showed that after the SE module pooling was added to the RIU-Net network, the utilization rate of the key features was raised. The specificity of patients in observation group was 98.7%, the accuracy was 93.7%, and the detected number was (1.6 ± 0.2). The specificity of patients in the control group was 93.2%, the accuracy was 87.6%, and the detected number was (1.3 ± 0.4). Obviously, the observation group was superior to the control group in all respects (P < 0.05). In conclusion, the optimized model demonstrates superb capabilities in image denoising and image segmentation. It can accurately extract the information to diagnose ACI, which is suggested clinically.

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Dual-source computed tomography image information under deep learning algorithm in evaluation of coronary artery lesion in children with Kawasaki disease

Cited by 2 publications

References 20 publications

[Retracted] Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning

[Retracted] Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning

Optimized Deconvolutional Algorithm‐based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction

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