Monitoring air pollutants, particularly PM2.5, which refers to fine particulate matter with a diameter of 2.5 µm or smaller, has become a focal point of environmental protection efforts worldwide. This study introduces the concept of state-trend awar...
Organ segmentation has become a preliminary task for computer-aided intervention, diagnosis, radiation therapy, and critical robotic surgery. Automatic organ segmentation from medical images is a challenging task due to the inconsistent shape and siz...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 13, 2024
Multimodal physiological signals play a pivotal role in drivers' perception of work stress. However, the scarcity of labels and the multitude of modalities render the utilization of physiological signals for driving cognitive alertness detection chal...
Computer methods and programs in biomedicine
Jun 11, 2024
BACKGROUND AND OBJECTIVE: Training convolutional neural networks based on large amount of labeled data has made great progress in the field of image segmentation. However, in medical image segmentation tasks, annotating the data is expensive and time...
Neural networks : the official journal of the International Neural Network Society
Jun 3, 2024
Image splicing, a prevalent method for image tampering, has significantly undermined image authenticity. Existing methods for Image Splicing Localization (ISL) struggle with challenges like limited accuracy and subpar performance when dealing with im...
The comprehensive integration of machine learning healthcare models within clinical practice remains suboptimal, notwithstanding the proliferation of high-performing solutions reported in the literature. A predominant factor hindering widespread adop...
Fast and accurate deformable image registration (DIR), including DIR uncertainty estimation, is essential for safe and reliable clinical deployment. While recent deep learning models have shown promise in predicting DIR with its uncertainty, challeng...
To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model.Two 3D UNets were established to predict ph...
Computer methods and programs in biomedicine
May 27, 2024
BACKGROUND AND OBJECTIVE: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisions by providing complementary information, particularly within high-r...
Neural networks : the official journal of the International Neural Network Society
May 21, 2024
This paper investigates a sliding mode control method for a class of uncertain delayed fractional-order reaction-diffusion memristor neural networks. Different from most existing literature on sliding mode control for fractional-order reaction-diffus...
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