IEEE/ACM transactions on computational biology and bioinformatics
Oct 9, 2023
Protein binding site prediction is an important prerequisite task of drug discovery and design. While binding sites are very small, irregular and varied in shape, making the prediction very challenging. Standard 3D U-Net has been adopted to predict b...
OBJECTIVE: Echocardiography, a critical tool for assessing left atrial (LA) volume, often relies on manual or semi-automated measurements. This study introduces a fully automated, real-time method for measuring LA volume in both 2-D and 3-D imaging, ...
The accurate delineation of organs-at-risk (OARs) is a crucial step in treatment planning during radiotherapy, as it minimizes the potential adverse effects of radiation on surrounding healthy organs. However, manual contouring of OARs in computed to...
Journal of magnetic resonance imaging : JMRI
Oct 6, 2023
BACKGROUND: The combination of anatomical MRI and deep learning-based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. However, studies assessing the effect ...
International journal of legal medicine
Oct 6, 2023
INTRODUCTION: Comparative radiography is a forensic identification and shortlisting technique based on the comparison of skeletal structures in ante-mortem and post-mortem images. The images (e.g., 2D radiographs or 3D computed tomographies) are manu...
BACKGROUND: Cone-beam computed tomography (CBCT) scanning is used for patient setup in image-guided radiotherapy. However, its inaccurate CT numbers limit its applicability in dose calculation and treatment planning.
Deep learning models excel at image recognition of macroscopic objects, but their applications to nanoscale particles are limited. Here, we explored their potential for source-distinguishing environmental particles. Transmission electron microscopy (...
Reducing CT radiation dose is an often proposed measure to enhance patient safety, which, however results in increased image noise, translating into degradation of clinical image quality. Several deep learning methods have been proposed for low-dose ...
IEEE journal of biomedical and health informatics
Oct 5, 2023
Distributed big data and digital healthcare technologies have great potential to promote medical services, but challenges arise when it comes to learning predictive model from diverse and complex e-health datasets. Federated Learning (FL), as a colla...
IEEE transactions on neural networks and learning systems
Oct 5, 2023
The nonuniform sampling (NUS) is a powerful approach to enable fast acquisition but requires sophisticated reconstruction algorithms. Faithful reconstruction from partially sampled exponentials is highly expected in general signal processing and many...
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