AIMC Topic: Deep Learning

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UTSRMorph: A Unified Transformer and Superresolution Network for Unsupervised Medical Image Registration.

IEEE transactions on medical imaging Feb 4, 2025
Complicated image registration is a key issue in medical image analysis, and deep learning-based methods have achieved better results than traditional methods. The methods include ConvNet-based and Transformer-based methods. Although ConvNets can eff...
Unsupervised Machine Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Brain Deep Learning Algorithms
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An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis.

IEEE transactions on medical imaging Feb 4, 2025
Time-series data such as fMRI and MEG carry a wealth of inherent spatio-temporal coupling relationship, and their modeling via deep learning is essential for uncovering biological mechanisms. However, current machine learning models for mining spatio...
Humans Brain Adult Male Deep Learning Female Young Adult Brain Mapping Connectome Image Processing, Computer-Assisted Adolescent Magnetic Resonance Imaging Magnetoencephalography Child
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Image recognition technology for bituminous concrete reservoir panel cracks based on deep learning.

PloS one Feb 4, 2025
Detecting cracks in asphalt concrete slabs is challenging due to environmental factors like lighting changes, surface reflections, and weather conditions, which affect image quality and crack detection accuracy. This study introduces a novel deep lea...
Hydrocarbons Image Processing, Computer-Assisted Algorithms Construction Materials Deep Learning
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A Multi-View Feature-Based Interpretable Deep Learning Framework for Drug-Drug Interaction Prediction.

Interdisciplinary sciences, computational life sciences Feb 3, 2025
Drug-drug interactions (DDIs) can result in deleterious consequences when patients take multiple medications simultaneously, emphasizing the critical need for accurate DDI prediction. Computational methods for DDI prediction have garnered recent atte...
Deep Learning Drug Interactions Humans Neural Networks, Computer
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Semi-supervised learning for multi-view and non-graph data using Graph Convolutional Networks.

Neural networks : the official journal of the International Neural Network Society Feb 3, 2025
Semi-supervised learning with a graph-based approach has become increasingly popular in machine learning, particularly when dealing with situations where labeling data is a costly process. Graph Convolution Networks (GCNs) have been widely employed i...
Supervised Machine Learning Algorithms Deep Learning Humans Neural Networks, Computer
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Prenatal Diagnostics Using Deep Learning: A Dual Approach to Plane Localization and Cerebellum Segmentation in Ultrasound Images.

Journal of clinical ultrasound : JCU Feb 3, 2025
OBJECTIVE: The fetal ultrasound examination is the significant task of mid-term pregnancy inspection and the accurate localization as well as the segmentation of the cerebellum is crucial for clinical diagnosis. This research focuses on developing de...
Humans Neural Networks, Computer Pregnancy Deep Learning Cerebellum Neurodevelopmental Disorders Female Ultrasonography, Prenatal
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Rational design and synthesis of pyrazole derivatives as potential SARS-CoV-2 M inhibitors: An integrated approach merging combinatorial chemistry, molecular docking, and deep learning.

Bioorganic & medicinal chemistry Feb 3, 2025
The global impact of SARS-CoV-2 has highlighted the urgent need for novel antiviral therapies. This study integrates combinatorial chemistry, molecular docking, and deep learning to design, evaluate and synthesize new pyrazole derivatives as potentia...
Structure-Activity Relationship Humans Pyrazoles Coronavirus 3C Proteases Deep Learning Molecular Docking Simulation Protease Inhibitors Combinatorial Chemistry Techniques Drug Design SARS-CoV-2 Antiviral Agents
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Rim learning framework based on TS-GAN: A new paradigm of automated glaucoma screening from fundus images.

Computers in biology and medicine Feb 3, 2025
Glaucoma detection from fundus images often relies on biomarkers such as the Cup-to-Disc Ratio (CDR) and Rim-to-Disc Ratio (RDR). However, precise segmentation of the optic cup and disc is challenging due to low-contrast boundaries and the interferen...
Neural Networks, Computer Glaucoma Image Processing, Computer-Assisted Fundus Oculi Image Interpretation, Computer-Assisted Humans Deep Learning Optic Disk
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S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification models.

Computers in biology and medicine Feb 3, 2025
Machine-learning-based automatic sleep stage scoring is a promising approach to enhance the time-consuming manual annotation process of polysomnography recordings. Although numerous algorithms have been proposed for this purpose, systematic explorati...
Deep Learning Signal Processing, Computer-Assisted Sleep Stages Humans Polysomnography Algorithms Databases, Factual
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Radiomics in glioma: emerging trends and challenges.

Annals of clinical and translational neurology Feb 3, 2025
Radiomics is a promising neuroimaging technique for extracting and analyzing quantitative glioma features. This review discusses the application, emerging trends, and challenges associated with using radiomics in glioma. Integrating deep learning alg...
Neuroimaging Humans Deep Learning Glioma Radiomics Brain Neoplasms
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