Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review
S Padash, MR Mohebbian, SJ Adams… - Pediatric …, 2022 - Springer
Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less
attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) …
attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) …
LDANet: Automatic lung parenchyma segmentation from CT images
Y Chen, L Feng, C Zheng, T Zhou, L Liu, P Liu… - Computers in Biology …, 2023 - Elsevier
Automatic segmentation of the lung parenchyma from computed tomography (CT) images is
helpful for the subsequent diagnosis and treatment of patients. In this paper, based on a …
helpful for the subsequent diagnosis and treatment of patients. In this paper, based on a …
Research and application advances of artificial intelligence in diagnosis and epidemic prediction of COVID-19
J Liu, J Wu, S Gong, W Hu, Y Zhou, S Hu - Fractals, 2023 - World Scientific
COVID-19 is a dangerous disease that directly damages human health, with the properties
of severely contagious and highly variable. It is endangering the health and safety of people …
of severely contagious and highly variable. It is endangering the health and safety of people …
PlaqueNet: deep learning enabled coronary artery plaque segmentation from coronary computed tomography angiography
L Wang, X Zhang, C Tian, S Chen, Y Deng… - Visual Computing for …, 2024 - Springer
Cardiovascular disease, primarily caused by atherosclerotic plaque formation, is a
significant health concern. The early detection of these plaques is crucial for targeted …
significant health concern. The early detection of these plaques is crucial for targeted …
Multi-scale feature fusion network with local attention for lung segmentation
Y Xie, Y Zhou, C Wang, Y Ma, M Yang - Signal Processing: Image …, 2023 - Elsevier
Computer-assisted medical care can benefit from the lung region segmentation method.
Numerous methods provide end-to-end solutions, these methods employ convolution neural …
Numerous methods provide end-to-end solutions, these methods employ convolution neural …
New attention-gated residual deep convolutional network for accurate lung segmentation in chest x-rays
Chest x-rays (CXRs) are broadly used in clinical practice to diagnose pulmonary diseases.
Developing reliable computer-aided diagnosis (CAD) systems to automate the interpretation …
Developing reliable computer-aided diagnosis (CAD) systems to automate the interpretation …
Efficient labeling for fine‐tuning chest X‐ray bone‐suppression networks for pediatric patients
W Xie, M Gan, X Tan, M Li, W Yang, W Wang - Medical Physics, 2024 - Wiley Online Library
Background Pneumonia, a major infectious cause of morbidity and mortality among children
worldwide, is typically diagnosed using low‐dose pediatric chest X‐ray [CXR (chest …
worldwide, is typically diagnosed using low‐dose pediatric chest X‐ray [CXR (chest …
CS-UNet: Cross-scale U-Net with Semantic-position dependencies for retinal vessel segmentation
Y Yang, S Yue, H Quan - Network: Computation in Neural Systems, 2024 - Taylor & Francis
Accurate retinal vessel segmentation is the prerequisite for early recognition and treatment
of retina-related diseases. However, segmenting retinal vessels is still challenging due to …
of retina-related diseases. However, segmenting retinal vessels is still challenging due to …