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A novel multi-branch architecture for state of the art robust detection of pathological phonocardiograms.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Heart auscultation is an inexpensive and fundamental technique to effectively diagnose cardiovascular disease. However, due to relatively high human error rates even when auscultation is performed by an experienced physician, and due to the not unive...

Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction.

BMC medical imaging
BACKGROUND: Efforts to reduce the radiation dose have continued steadily, with new reconstruction techniques. Recently, image denoising algorithms using artificial neural networks, termed deep learning reconstruction (DLR), have been applied to CT im...

Attention-Based Joint Training of Noise Suppression and Sound Event Detection for Noise-Robust Classification.

Sensors (Basel, Switzerland)
Sound event detection (SED) recognizes the corresponding sound event of an incoming signal and estimates its temporal boundary. Although SED has been recently developed and used in various fields, achieving noise-robust SED in a real environment is t...

Feasibility evaluation of PET scan-time reduction for diagnosing amyloid-β levels in Alzheimer's disease patients using a deep-learning-based denoising algorithm.

Computers in biology and medicine
PURPOSE: To shorten positron emission tomography (PET) scanning time in diagnosing amyloid-β levels thus increasing the workflow in centers involving Alzheimer's Disease (AD) patients.

Adaptive investigation of the optical properties of polymer fibers from mixing noisy phase shifting microinterferograms using deep learning algorithms.

Microscopy research and technique
In this article, an adaptive denoising method is suggested to accurate investigate the optical and structural features of polymeric fibers from noisy phase shifting microinterferograms. The mixed class of noise that may produce in the phase-shifting ...

Comparison of different deep learning architectures for synthetic CT generation from MR images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Among the different available methods for synthetic CT generation from MR images for the task of MR-guided radiation planning, the deep learning algorithms have and do outperform their conventional counterparts. In this study, we investigate...

Recovery of Ionospheric Signals Using Fully Convolutional DenseNet and Its Challenges.

Sensors (Basel, Switzerland)
The technique of active ionospheric sounding by ionosondes requires sophisticated methods for the recovery of experimental data on ionograms. In this work, we applied an advanced algorithm of deep learning for the identification and classification of...

A Novel Medical Image Denoising Method Based on Conditional Generative Adversarial Network.

Computational and mathematical methods in medicine
Medical image quality is highly relative to clinical diagnosis and treatment, leading to a popular research topic of medical image denoising. Image denoising based on deep learning methods has attracted considerable attention owing to its excellent a...

Imaging in focus: An introduction to denoising bioimages in the era of deep learning.

The international journal of biochemistry & cell biology
Fluorescence microscopy enables the direct observation of previously hidden dynamic processes of life, allowing profound insights into mechanisms of health and disease. However, imaging of live samples is fundamentally limited by the toxicity of the ...

DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images.

IEEE journal of biomedical and health informatics
Multi-modal medical image fusion is a challenging yet important task for precision diagnosis and surgical planning in clinical practice. Although single feature fusion strategy such as Densefuse has achieved inspiring performance, it tends to be not ...