A Displacement Estimated Method for Real Time Tissue Ultrasound Elastography

Li, Hong An; Zhang, Min; Yu, Keping; Qi, Xin; Tong, Jianfeng

doi:10.1007/s11036-021-01735-3

Cited by 8 publications

(5 citation statements)

References 42 publications

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“…In traditional algorithms, style is generally understood as the texture characteristics of the image. By constructing mathematical or statistical models, the original image is re-sampled to continuously generate new pixels or pixel blocks and then generate style transfer images [ 9 , 10 ]. This algorithm has the advantages of simplicity and fast running speed, but due to the overall color migration, it cannot perform good image style transfer for images with rich color content.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Neural Network‐Based Mapping Mining of Image Style Transfer in Big Data Systems

Zheng

et al. 2021

Computational Intelligence and Neuroscience

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Image style transfer can realize the mutual transfer between different styles of images and is an essential application for big data systems. The use of neural network-based image data mining technology can effectively mine the useful information in the image and improve the utilization rate of information. However, when using the deep learning method to transform the image style, the content information is often lost. To address this problem, this paper introduces L1 loss on the basis of the VGG-19 network to reduce the difference between image style and content and adds perceptual loss to calculate the semantic information of the feature map to improve the model’s perceptual ability. Experiments show that the proposal in this paper improves the ability of style transfer, while maintaining image content information. The stylization of the improved model can better meet people’s requirements for stylization, and the evaluation indexes of structural similarity, cosine similarity, and mutual information value have increased by 0.323%, 0.094%, and 3.591%, respectively.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Neural Network‐Based Mapping Mining of Image Style Transfer in Big Data Systems

Zheng

et al. 2021

Computational Intelligence and Neuroscience

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“…The collection of hemolysis images may be affected by uncontrollable factors such as light and photo angle, leading to the phenomenon of extremely concentrated grayscale of hemolysis images or unobvious feature areas [ 17 , 18 ]. Therefore, image enhancement of the collected hemolysis image can cause different angle features and detail features of the image to appear, reduce the impact of irrelevant information, promote the model to extract more features of the image, and identify hemolysis from multiple features.…”

Section: Methodsmentioning

confidence: 99%

“…Let the formula of sample x generated by a group of random noise z after the generator [ 17 , 18 ] be as follows:

where g ( x )is the final output after several convolution, pooling, and activation operations (see Equations ( 14 ) and ( 15 ), function with discriminator D f ( x , θ g ).…”

Section: Methodsmentioning

confidence: 99%

A Hemolysis Image Detection Method Based on GAN-CNN-ELM

Shi

Deng

Fang

et al. 2022

Computational and Mathematical Methods in Medicine

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Since manual hemolysis test methods are given priority with practical experience and its cost is high, the characteristics of hemolysis images are studied. A hemolysis image detection method based on generative adversarial networks (GANs) and convolutional neural networks (CNNs) with extreme learning machine (ELM) is proposed. First, the image enhancement and data enhancement are performed on a sample set, and GAN is used to expand the sample data volume. Second, CNN is used to extract the feature vectors of the processed images and label eigenvectors with one-hot encoding. Third, the feature matrix is input to the map in the ELM network to minimize the error and obtain the optimal weight by training. Finally, the image to be detected is input to the trained model, and the image with the greatest probability is selected as the final category. Through model comparison experiments, the results show that the hemolysis image detection method based on the GAN-CNN-ELM model is better than GAN-CNN, GAN-ELM, GAN-ELM-L1, GAN-SVM, GAN-CNN-SVM, and CNN-ELM in accuracy and speed, and the accuracy rate is 98.91%.

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“…Bio-inspired modeling researches computerized solutions from living phenomena or biological systems. They have great potential applications in areas such as Internet of Things (IoT) [16][17][18][19][20], Internet of Vehicles (IoV) [21,22], block chain [23][24][25][26], image processing [27][28][29][30][31], privacy-preserving [32][33][34], unmanned aerial vehicles (UAVs) [35][36][37][38], medical treatment [39][40][41][42][43] and communication [44,45]. An increasing number of bio-inspired algorithms have been developed in recent decades.…”

Section: Introductionmentioning

confidence: 99%

Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

Zhao¹,

Zhang²,

Hua³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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Bio-inspired computer modelling brings solutions from the living phenomena or biological systems to engineering domains. To overcome the obstruction problem of large-scale wind power consumption in Northwest China, this paper constructs a bio-inspired computer model. It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load. First, the principle of wind power obstruction with the involvement of a high-energy load is examined in this work. In this step, highenergy load model with different regulation characteristics is established. Then, considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed, a multi-time scale model of coordination optimization is built. An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs, as well as to find the most optimal energy configuration within the system. Lastly, we take an example of regional power grid in Gansu Province for simulation analysis. Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system's operational cost.

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A Displacement Estimated Method for Real Time Tissue Ultrasound Elastography

Cited by 8 publications

References 42 publications

[Retracted] Neural Network‐Based Mapping Mining of Image Style Transfer in Big Data Systems

[Retracted] Neural Network‐Based Mapping Mining of Image Style Transfer in Big Data Systems

A Hemolysis Image Detection Method Based on GAN-CNN-ELM

Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

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