AIMC Topic: Neural Networks, Computer

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Unsupervised 3D Lung Segmentation by Leveraging 2D Segment Anything Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Lung segmentation is the first important step for lung nodule detection and lung cancer analysis. Deep neural networks have achieved state-of-the-art for most tasks in medical image analysis, including lung segmentation. However, training a deep lear...
Lung Neoplasms Lung Imaging, Three-Dimensional Unsupervised Machine Learning Deep Learning Algorithms Humans Neural Networks, Computer Tomography, X-Ray Computed
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Instance-Wise MRI Reconstruction Based on Self-Supervised Implicit Neural Representation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Accelerated MRI involves a trade-off between sampling sufficiency and acquisition time. Supervised deep learning methods have shown great success in MRI reconstruction from under-sampled measurements, but they typically require a large set of fully-s...
Algorithms Brain Humans Neural Networks, Computer Reproducibility of Results Magnetic Resonance Imaging Image Processing, Computer-Assisted Deep Learning Supervised Machine Learning
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Fast Diffeomorphic Image Registration using Patch based Fully Convolutional Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Diffeomorphic image registration is a fundamental step in medical image analysis, owing to its capability to ensure the invertibility of transformations and preservation of topology. Currently, unsupervised learning-based registration techniques prim...
Magnetic Resonance Imaging Unsupervised Machine Learning Algorithms Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Bi-Stream Adaptation Network for Motor Imagery Decoding.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Neural activities in distinct brain regions variably contribute to the formation of motor imagery (MI). Utilizing the hidden contextual information can thereby enhance network performance by having a comprehensive understanding of MI. Besides, due to...
Neural Networks, Computer Algorithms Humans Signal Processing, Computer-Assisted Imagination Brain Electroencephalography
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A Method of Cross-Subject Transfer Learning for Ultra Short Time SSVEP Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The steady-state visual evoked potentials (SSVEP) based brain-computer interfaces (BCIs) require extensive training data for efficient classification, but existing algorithms struggle with ultra short time inputs (less than 0.2 seconds), limiting the...
Brain-Computer Interfaces Evoked Potentials, Visual Electroencephalography Signal Processing, Computer-Assisted Humans Algorithms Machine Learning Neural Networks, Computer Time Factors
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GANs-guided Conditional Diffusion Model for Synthesizing Contrast-enhanced Computed Tomography Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
In contrast to non-contrast computed tomography (NC-CT) scans, contrast-enhanced (CE) CT scans can highlight discrepancies between abnormal and normal areas, commonly used in clinical diagnosis of focal liver lesions. However, the use of contrast age...
Contrast Media Diffusion Humans Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted Algorithms
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An Attention-Based Hybrid Deep Learning Approach for Patient-Specific, Cross-Patient, and Patient-Independent Seizure Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Automatic detection of epilepsy plays a crucial role in diagnosing and treatment of patients, while most current methods rely on patient-specific models and have shown promising results, which is not suitable for clinical application, especially when...
Humans Neural Networks, Computer Electroencephalography Seizures Signal Processing, Computer-Assisted Algorithms Deep Learning Attention
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EEG Emotion Recognition Based on 3D-CTransNet.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Emotion recognition is of great significance for brain-computer interface and emotion computing, and EEG plays a key role in this field. However, the current design of brain computer interface deep learning model is faced with algorithmic or structur...
Deep Learning Emotions Neural Networks, Computer Signal Processing, Computer-Assisted Brain-Computer Interfaces Algorithms Humans Electroencephalography
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A CNN and Transformer Hybrid Network for Multi-Class Arrhythmia Detection from Photoplethysmography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Photoplethysmography (PPG)-based arrhythmia detection methods have gained attention with wearable technology, enabling early detection of undiagnosed arrhythmias. Existing methods excel in single arrhythmia detection but struggle with multiple arrhyt...
Algorithms Photoplethysmography Signal Processing, Computer-Assisted Humans Arrhythmias, Cardiac Neural Networks, Computer
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Structure-aware deep learning model for peptide toxicity prediction.

Protein science : a publication of the Protein Society Jul 1, 2024
Antimicrobial resistance is a critical public health concern, necessitating the exploration of alternative treatments. While antimicrobial peptides (AMPs) show promise, assessing their toxicity using traditional wet lab methods is both time-consuming...
Deep Learning Hemolysis Antimicrobial Peptides Neural Networks, Computer
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