IEEE journal of biomedical and health informatics
Jan 7, 2025
In semi-supervised medical image segmentation, the issue of fuzzy boundaries for segmented objects arises. With limited labeled data and the interaction of boundaries from different segmented objects, classifying segmentation boundaries becomes chall...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Facial expressions vary with different health conditions, making a facial expression recognition (FER) system valuable within a healthcare framework. Achieving accurate recognition of facial expressions is a considerable challenge due to the difficul...
IEEE journal of biomedical and health informatics
Jan 7, 2025
In recent years, encoder-decoder-based network structures have been widely used in designing medical image segmentation models. However, these methods still face some limitations: 1) The network's feature extraction capability is limited, primarily d...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Proposal-free instance segmentation methods have significantly advanced the field of biological image analysis. Recently, the Segment Anything Model (SAM) has shown an extraordinary ability to handle challenging instance boundaries. However, directly...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Typically developing infants, between the corrected age of 9-20 weeks, produce fidgety movements. These movements can be identified with the General Movement Assessment, but their identification requires trained professionals to conduct the assessmen...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Diffusion tensor imaging (DTI) is a prevalent magnetic resonance imaging (MRI) technique, widely used in clinical and neuroscience research. However, the reliability of DTI is affected by the low signal-to-noise ratio inherent in diffusion-weighted (...
IEEE journal of biomedical and health informatics
Jan 7, 2025
The excessive consumption of marijuana can induce substantial psychological and social consequences. In this investigation, we propose an elucidative framework termed high-order graph attention neural networks (HOGANN) for the classification of Marij...
IEEE transactions on neural networks and learning systems
Jan 7, 2025
Medical image segmentation is an important task in medical imaging, as it serves as the first step for clinical diagnosis and treatment planning. While major success has been reported using deep learning supervised techniques, they assume a large and...
IEEE transactions on neural networks and learning systems
Jan 7, 2025
Introducing deep learning technologies into the medical image processing field requires accuracy guarantee, especially for high-resolution images relayed through endoscopes. Moreover, works relying on supervised learning are powerless in the case of ...
Biomedizinische Technik. Biomedical engineering
Jan 6, 2025
OBJECTIVES: Diabetic retinopathy (DR) is associated with long-term diabetes and is a leading cause of blindness if it is not diagnosed early. The rapid growth of deep learning eases the clinicians' DR diagnosing procedure. It automatically extracts t...
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