Journal of medical engineering & technology
Feb 14, 2025
Developing a robust and effective technique is crucial for interpreting a user's brainwave signals accurately in the realm of biomedical signal processing. The variability and uncertainty present in EEG patterns over time, compounded by noise, pose n...
Journal of medical engineering & technology
Feb 14, 2025
The work proposes a methodology for five different classes of ECG signals. The methodology utilises moving average filter and discrete wavelet transformation for the remove of baseline wandering and powerline interference. The preprocessed signals ar...
The decomposition of a biomolecular complex into domains is an important step to investigate biological functions and ease structure determination. A successful approach to do so is the SPECTRUS algorithm, which provides a segmentation based on spect...
Medical & biological engineering & computing
Feb 13, 2025
Accurate three-dimensional (3D) segmentation of hepatic vascular networks is crucial for supporting ultrasound-mediated theranostics for liver diseases. Despite advancements in deep learning techniques, accurate segmentation remains challenging due t...
Alzheimer's Disease (AD) is a significant cause of mortality in elderly people. The diagnosing and classification of AD using conventional manual operation is a challenging issue. Here, a novel scheme, namely Recurrent Prototypical Network with Taylo...
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions. Counterfactual reasoning has rec...
OBJECTIVE: To evaluate the performance of an automated two-step model interpreting pediatric temporomandibular joint (TMJ) magnetic resonance imaging (MRI) using artificial intelligence (AI). Using deep learning techniques, the model first automatica...
Brain tumors are incredibly harmful and can drastically reduce life expectancy. Most researchers use magnetic resonance (MR) scans to detect tumors because they can provide detailed images of the affected area. Recently, AI-based deep learning method...
Journal of applied clinical medical physics
Feb 13, 2025
PURPOSE: Deep learning-based segmentation of organs-at-risk (OAR) is emerging to become mainstream in clinical practice because of the superior performance over atlas and model-based autocontouring methods. While several commercial deep learning-base...
Monitoring nociception under general anesthesia remains challenging due to the complexity of pain pathways and the limitations of single-parameter methods. In this study, we introduce a multimodal approach that integrates electroencephalogram (EEG), ...
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