IEEE journal of biomedical and health informatics
Nov 6, 2024
The field of 3D medical image segmentation is witnessing a growing trend in the utilization of combined networks that integrate convolutional neural networks and transformers. Nevertheless, prevailing hybrid networks are confronted with limitations i...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Multi-parametric magnetic resonance imaging (mpMRI) exams have various series types acquired with different imaging protocols. The DICOM headers of these series often have incorrect information due to the sheer diversity of protocols and occasional t...
IEEE journal of biomedical and health informatics
Nov 6, 2024
In radiology, particularly in lung cancer diagnosis, diagnostic errors and cognitive biases pose substantial challenges. These issues, including perceptual errors, interpretive mistakes, and cognitive biases such as anchoring and premature closure, a...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Multi-modality image registration is an important task in medical imaging because it allows for information from different domains to be correlated. Histopathology plays a crucial role in oncologic surgery as it is the gold standard for investigating...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Automated retinal vessel segmentation is crucial for computer-aided clinical diagnosis and retinopathy screening. However, deep learning faces challenges in extracting complex intertwined structures and subtle small vessels from densely vascularized ...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Walking-assistive devices require adaptive control methods to ensure smooth transitions between various modes of locomotion. For this purpose, detecting human locomotion modes (e.g., level walking or stair ascent) in advance is crucial for improving ...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Novel drug-target interaction (DTI) prediction is crucial in drug discovery and repositioning. Recently, graph neural network (GNN) has shown promising results in identifying DTI by using thresholds to construct heterogeneous graphs. However, an empi...
IEEE journal of biomedical and health informatics
Nov 6, 2024
In response to increasing data privacy regulations, this work examines the use of federated learning for deep residual networks to diagnose cardiac abnormalities from electrocardiogram (ECG) data. This approach allows medical institutions to collabor...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Uncertainty quantification is critical for ensuring the safety of deep learning-enabled health diagnostics, as it helps the model account for unknown factors and reduces the risk of misdiagnosis. However, existing uncertainty quantification studies o...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Medical image processing plays an important role in the interaction of real world and metaverse for healthcare. Self-supervised denoising based on sparse coding methods, without any prerequisite on large-scale training samples, has been attracting ex...
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