Bilateral Supervision Network for Semi-Supervised Medical Image Segmentation

Bilateral Supervision Network for Semi-Supervised Medical Image Segmentation

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Life Sciences, Bioengineering,
semi-supervised learning   bilateral supervision   medical image segmentation   EMA   adversarial learning  

Research Background and Motivation Medical image segmentation is of great significance in the image analysis of anatomical structures and lesion areas, as well as in clinical diagnosis. However, existing fully supervised learning methods rely on a large amount of annotated data, and obtaining pixel-level annotated data for medical images is costly ...

Whole Reconstruction-Free System Design for Direct Positron Emission Imaging from Image Generation to Attenuation Correction

Whole Reconstruction-Free System Design for Direct Positron Emission Imaging from Image Generation to Attenuation Correction

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Life Sciences, Bioengineering, Biophysics,
reconstruction-free system   positron emission imaging   image generation   attenuation correction   µcompton imaging  

Background Introduction A hundred years ago, Hevesy first proposed using radioactive tracers as biological markers in plants, later validated through experiments in rats. This discovery propelled the development of nuclear medicine and molecular imaging in the biomedical field, making it possible to quantitatively visualize biological processes at ...

Evoked Component Analysis (ECA): Decomposing the Functional Ultrasound Signal with GLM-Regularization

Information Science, Automation, Artificial Intelligence, Medicine, Medical Imaging,
Evoked Component Analysis   Functional Ultrasound   GLM Regularization   Neuroimaging   Low-Rank Decomposition  

Evoked Component Analysis (ECA): Decomposing Functional Ultrasound Signals Based on GLM Regularization Background The analysis of functional neuroimaging data aims to uncover spatial and temporal patterns of brain activity. Existing data analysis methods mainly fall into two categories: fully data-driven analysis methods and methods that rely on pr...

AI-based Denoising of Head Impact Kinematics Measurements with Convolutional Neural Network for Traumatic Brain Injury Prediction

Information Science, Artificial Intelligence, Medicine, Neurosurgery, Life Sciences, Bioengineering,
AI   Convolutional Neural Network   Head Impact   Traumatic Brain Injury   Denoising   Kinematics Measurements  

Research and Application of Denoising Head Impact Kinematics Measurement Based on Convolutional Neural Networks Research Background Mild Traumatic Brain Injury (MTBI) is a global health threat. Humans often face the risk of MTBI in situations such as falls, traffic accidents, and sports. According to statistics, there were over 27 million brain inj...

Joint B0 and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning

Joint B0 and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Life Sciences, Biophysics,
low-field MRI   physics-informed   deep learning   image reconstruction   unrolled optimization   field inhomogeneities  

Low-Field MRI Image Reconstruction Using Physics-Informed Deep Learning Background: The application of magnetic resonance imaging (MRI) technology in low-field magnetic resonance imaging has gained increasing attention in recent years. Low-field MRI, due to its low cost and simplified maintenance, is considered to have a broad application prospect ...

Heart Sound Abnormality Detection from Multi-Institutional Collaboration: Introducing a Federated Learning Framework

Heart Sound Abnormality Detection from Multi-Institutional Collaboration: Introducing a Federated Learning Framework

Information Science, Artificial Intelligence, Medicine, Cardiovascular System,
Heart Sound Abnormality   Multi-Institutional Collaboration   Federated Learning   Privacy Protection   Deep Learning  

Academic Background Cardiovascular diseases (CVDs) have become one of the leading causes of death, particularly within the elderly population, making cardiovascular health a pressing societal concern. Early screening, diagnosis, and prognosis management are crucial for preventing hospitalizations. Heart sound signals carry rich physiological and pa...