AIMC Topic: Wavelet Analysis

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Towards dental diagnostic systems: Synergizing wavelet transform with generative adversarial networks for enhanced image data fusion.

Computers in biology and medicine Oct 2, 2024
The advent of precision diagnostics in pediatric dentistry is shifting towards ensuring early detection of dental diseases, a critical factor in safeguarding the oral health of the younger population. In this study, an innovative approach is introduc...
Child Radiography, Panoramic Wavelet Analysis Humans Neural Networks, Computer
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Adaptive wavelet-VNet for single-sample test time adaptation in medical image segmentation.

Medical physics Oct 1, 2024
BACKGROUND: In medical image segmentation, a domain gap often exists between training and testing datasets due to different scanners or imaging protocols, which leads to performance degradation in deep learning-based segmentation models. Given the hi...
Time Factors Image Processing, Computer-Assisted Wavelet Analysis Humans Deep Learning
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A Lightweight Convolutional Neural Network-Reformer Model for Efficient Epileptic Seizure Detection.

International journal of neural systems Sep 30, 2024
A real-time and reliable automatic detection system for epileptic seizures holds significant value in assisting physicians with rapid diagnosis and treatment of epilepsy. Aiming to address this issue, a novel lightweight model called Convolutional Ne...
Humans Neural Networks, Computer Electroencephalography Wavelet Analysis Epilepsy Seizures Signal Processing, Computer-Assisted Sensitivity and Specificity
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A Learnable and Explainable Wavelet Neural Network for EEG Artifacts Detection and Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 16, 2024
Electroencephalography (EEG) artifacts are very common in clinical diagnosis and can heavily impact diagnosis. Manual screening of artifact events is labor-intensive with little benefit. Therefore, exploring algorithms for automatic detection and cla...
Reproducibility of Results Electroencephalography Artifacts Wavelet Analysis Signal Processing, Computer-Assisted Machine Learning Algorithms Humans Neural Networks, Computer
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Illumination-aware divide-and-conquer network for improperly-exposed image enhancement.

Neural networks : the official journal of the International Neural Network Society Sep 12, 2024
Improperly-exposed images often have unsatisfactory visual characteristics like inadequate illumination, low contrast, and the loss of small structures and details. The mapping relationship from an improperly-exposed condition to a well-exposed one m...
Algorithms Image Processing, Computer-Assisted Image Enhancement Wavelet Analysis Lighting Humans Neural Networks, Computer
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A deep learning phase-based solution in 2D echocardiography motion estimation.

Physical and engineering sciences in medicine Sep 12, 2024
In this paper, we propose a new deep learning method based on Quaternion Wavelet Transform (QWT) phases of 2D echocardiographic sequences to estimate the motion and strain of myocardium. The proposed method considers intensity and phases gained from ...
Image Processing, Computer-Assisted Wavelet Analysis Movement Echocardiography Deep Learning Humans Algorithms
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Prediction of anhedonia in patients with first-episode schizophrenia using a Wavelet-ALFF-based Support vector regression model.

Neuroscience Sep 5, 2024
Anhedonia is one of the core features of the negative symptoms of schizophrenia and can be extremely burdensome. Our study applied resting-state functional magnetic resonance imaging (fMRI)-based support vector regression (SVR) to predict anhedonia i...
Adult Male Support Vector Machine Female Young Adult Schizophrenia Anhedonia Wavelet Analysis Magnetic Resonance Imaging Brain Mapping Humans Brain Schizophrenic Psychology
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Deep learning method with integrated invertible wavelet scattering for improving the quality ofcardiac DTI.

Physics in medicine and biology Sep 5, 2024
Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations ofcardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scatterin...
Heart Signal-To-Noise Ratio Diffusion Tensor Imaging Diastole Wavelet Analysis Deep Learning Image Processing, Computer-Assisted Humans
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Automated Crack Detection in Monolithic Zirconia Crowns Using Acoustic Emission and Deep Learning Techniques.

Sensors (Basel, Switzerland) Aug 31, 2024
Monolithic zirconia (MZ) crowns are widely utilized in dental restorations, particularly for substantial tooth structure loss. Inspection, tactile, and radiographic examinations can be time-consuming and error-prone, which may delay diagnosis. Conseq...
Deep Learning Wavelet Analysis Acoustics Humans Crowns Neural Networks, Computer Zirconium
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Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.

BMC medical imaging Aug 28, 2024
Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominently found in diabetic patients. The early identification of DR/DME grades facilitates the devising of an appropriate treatment plan, which ultimately ...
Image Interpretation, Computer-Assisted Wavelet Analysis Algorithms Macular Edema Humans Diabetic Retinopathy Neural Networks, Computer
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