An accurate paradigm for denoising degraded ultrasound images based on artificial intelligence systems
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Summary
This research proposes an accurate ultrasound image denoising strategy based on firstly detecting the noise type, then, suitable denoising methods can be applied for each corruption to demonstrate efficacy of the proposed detect‐then‐denoise system.
- Type
- article
- Published
- 2024-08-15
- Cited by
- 2
- References
- 48
- Access
- Open access
- OpenAlex
- https://openalex.org/W4401594908
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:271873345
Keywords
Artificial intelligence, Computer science, Support vector machine, Convolutional neural network, Speckle noise
References
- An improved windowed Fourier transform filter algorithm
- Speckle reduction and deblurring of ultrasound images using artificial neural network
- Performance analysis of speckle ultrasound image filtering
- Homomorphic wavelet thresholding technique for denoising medical ultrasound images
- Image denoising with block-matching and 3D filtering
- Medical ultrasound image compression using joint optimization of thresholding quantization and best-basis selection of wavelet packets
- Weighted Nuclear Norm Minimization with Application to Image Denoising
- Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.
- Intelligent estimation of noise and blur variances using ANN for the restoration of ultrasound images.
- A deep learning approach to ultrasound image recovery
- Real-time salt and pepper noise removal from medical images using a modified weighted average filtering
- Performance Enhancement and Analysis of Filters in Ultrasound Image Denoising
- A High-Precision US-Guided Robot-Assisted HIFU Treatment System for Breast Cancer
- Ultrasound Image Enhancement Using Structure Oriented Adversarial Network
- Denoising of ultrasound images affected by combined speckle and Gaussian noise
- Insights Into LSTM Fully Convolutional Networks for Time Series Classification
- Editorial on the Current Role of Ultrasound
- Speckle Noise Reduction in Ultrasound Images for Improving the Metrological Evaluation of Biomedical Applications: An Overview
- Despeckling of clinical ultrasound images using deep residual learning
- Accurate automatic detection of acute lymphatic leukemia using a refined simple classification
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