How to Analyze the Neurodynamic Characteristics of Pulse-Coupled Neural Networks? A Theoretical Analysis and Case Study of Intersecting Cortical Model

Jin, Xin; Zhou, Dongming; Jiang, Qian; Chu, Xing; Yao, Shaowen; Li, Keqin; Zhou, Wei

doi:10.1109/tcyb.2020.3043233

Cited by 3 publications

(7 citation statements)

References 51 publications

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“…e AUC of ROC for the diagnosis of AKI was drawn on the 2 nd day, 4 th day, and 6 th day of entering the ICU [20]. e patient with AKI was defined as a positive index as 1, and the ROC curves of RRI on the 2 nd day, 4 th day, and 6 th day after entering the ICU were drawn to the diagnosis of AKI.…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Pulse Coupled Neural Network Algorithm in the Diagnosis and Treatment of Severe Sepsis Complicated with Acute Kidney Injury under Ultrasound Image

Ying

Chen

Pan

et al. 2021

Journal of Healthcare Engineering

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The objective of this study was to explore the diagnosis of severe sepsis complicated with acute kidney injury (AKI) by ultrasonic image information based on the artificial intelligence pulse coupled neural network (PCNN) algorithm. In this study, an algorithm of ultrasonic image information enhancement based on the artificial intelligence PCNN was constructed and compared with the histogram equalization algorithm and linear transformation algorithm. After that, it was applied to the ultrasonic image diagnosis of 20 cases of severe sepsis combined with AKI in hospital. The condition of each patient was diagnosed by ultrasound image performance, change of renal resistance index (RRI), ultrasound score, and receiver operator characteristic curve (ROC) analysis. It was found that the histogram distribution of this algorithm was relatively uniform, and the information of each gray level was obviously retained and enhanced, which had the best effect in this algorithm; there was a marked individual difference in the values of RRI. Overall, the values of RRI showed a slight upward trend after admission to the intensive care unit (ICU). The RRI was taken as the dependent variable, time as the fixed-effect model, and patients as the random effect; the parameter value of time was between 0.012 and 0.015, p = 0.000 < 0.05 . Besides, there was no huge difference in the ultrasonic score among different time measurements (t = 1.348 and p = 0.128 > 0.05 ). The area under the ROC curve of the RRI for the diagnosis of AKI at the 2nd day, 4th day, and 6th day was 0.758, 0.841, and 0.856, respectively, which was all greater than 0.5 ( p < 0.05 ). In conclusion, the proposed algorithm in this study could significantly enhance the amount of information in ultrasound images. In addition, the change of RRI values measured by ultrasound images based on the artificial intelligence PCNN was associated with AKI.

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Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Pulse Coupled Neural Network Algorithm in the Diagnosis and Treatment of Severe Sepsis Complicated with Acute Kidney Injury under Ultrasound Image

Ying

Chen

Pan

et al. 2021

Journal of Healthcare Engineering

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“…20,23,24,[32][33][34][35][36][37][38][39][40][41][42][43][44] PCNN is consistent with HVS in processing digital images, 34,40 Weber-Fechner law and Mach band effect have been well simulated, but there are many network parameters. 18,19 Kinser et al proposed simplified pulse-coupled neural network (SPN) 41 model with only one weight matrix and a constant dynamic threshold for neurons. SPN has similar performance to PCNN in edge extraction and image segmentation.…”

Section: Hybrid Methodsmentioning

confidence: 99%

“…In general, parameters are preset according to specific situations. 18,19 A single neuron in PCNN contains three inputs, namely external stimulus input, linking synaptic input, and feedback synaptic input. 43 These three inputs are modulated and expressed as neuronal membrane potential.…”

Section: Model Of Pcnnmentioning

confidence: 99%

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Low-light image enhancement using negative feedback pulse coupled neural network

Gao,

Zhang,

Chen

et al. 2024

J. Electron. Imag.

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“…In recent years, many MEF algorithms have been developed. Like multi-source image fusion (Jin et al, 2021a ), MEF algorithms are usually divided into four categories (Liu et al, 2020 ): spatial domain methods, transform domain methods, the combination of spatial domain and transform domain methods and deep learning methods (Jin et al, 2021b ). This article mainly studies the MEF method in spatial domain,these methods mainly focus on providing the weighted sum of the input exposures image to obtain the fused image.…”

Section: Introductionmentioning

confidence: 99%

Multi-Exposure Image Fusion Algorithm Based on Improved Weight Function

Wang

Xiao

et al. 2022

Front. Neurorobot.

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High-dynamic-range (HDR) image has a wide range of applications, but its access is limited. Multi-exposure image fusion techniques have been widely concerned because they can obtain images similar to HDR images. In order to solve the detail loss of multi-exposure image fusion (MEF) in image reconstruction process, exposure moderate evaluation and relative brightness are used as joint weight functions. On the basis of the existing Laplacian pyramid fusion algorithm, the improved weight function can capture the more accurate image details, thereby making the fused image more detailed. In 20 sets of multi-exposure image sequences, six multi-exposure image fusion methods are compared in both subjective and objective aspects. Both qualitative and quantitative performance analysis of experimental results confirm that the proposed multi-scale decomposition image fusion method can produce high-quality HDR images.

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How to Analyze the Neurodynamic Characteristics of Pulse-Coupled Neural Networks? A Theoretical Analysis and Case Study of Intersecting Cortical Model

Cited by 3 publications

References 51 publications

Artificial Intelligence Pulse Coupled Neural Network Algorithm in the Diagnosis and Treatment of Severe Sepsis Complicated with Acute Kidney Injury under Ultrasound Image

Artificial Intelligence Pulse Coupled Neural Network Algorithm in the Diagnosis and Treatment of Severe Sepsis Complicated with Acute Kidney Injury under Ultrasound Image

Low-light image enhancement using negative feedback pulse coupled neural network

Multi-Exposure Image Fusion Algorithm Based on Improved Weight Function

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