AIMC Topic: Deep Learning

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Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach.

BMC medical imaging Feb 4, 2025
BACKGROUND: Computed tomography attenuation correction (CTAC) is commonly used in cardiac SPECT imaging to reduce soft-tissue attenuation artifacts. However, CTAC is prone to inaccuracies due to CT artifacts and SPECT-CT mismatch, along with addition...
Middle Aged Deep Learning Image Processing, Computer-Assisted Heart Artifacts Tomography, Emission-Computed, Single-Photon Female Aged Male Humans Tomography, X-Ray Computed
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ThyroNet-X4 genesis: an advanced deep learning model for auxiliary diagnosis of thyroid nodules' malignancy.

Scientific reports Feb 4, 2025
Thyroid nodules are a common endocrine condition, and accurate differentiation between benign and malignant nodules is essential for making appropriate treatment decisions. Traditional ultrasound-based diagnoses often depend on the expertise of physi...
Thyroid Neoplasms Ultrasonography Thyroid Nodule Humans Deep Learning Thyroid Gland Diagnosis, Differential
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Advances in colorectal cancer diagnosis using optimal deep feature fusion approach on biomedical images.

Scientific reports Feb 4, 2025
Colorectal cancer (CRC) is the second popular cancer in females and third in males, with an increased number of cases. Pathology diagnoses complemented with predictive and prognostic biomarker information is the first step for personalized treatment....
Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Colorectal Neoplasms Male Machine Learning Algorithms Female Humans Artificial Intelligence
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Capsule neural network and adapted golden search optimizer based forest fire and smoke detection.

Scientific reports Feb 4, 2025
Forest fires represent a major risk to both ecosystems and human health that rising frequency of it exacerbates global warming. This study introduces an innovative methodology for detecting forest fires and smoke using an enhanced capsule neural netw...
Humans Neural Networks, Computer Algorithms Deep Learning Fires Forests Wildfires Smoke
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Automatic cervical lymph nodes detection and segmentation in heterogeneous computed tomography images using deep transfer learning.

Scientific reports Feb 4, 2025
To develop a deep learning model using transfer learning for automatic detection and segmentation of neck lymph nodes (LNs) in computed tomography (CT) images, the study included 11,013 annotated LNs with a short-axis diameter ≥ 3 mm from 626 head an...
Lymphatic Metastasis Head and Neck Neoplasms Neck Sensitivity and Specificity Male Middle Aged Deep Learning Image Processing, Computer-Assisted Lymph Nodes Humans Tomography, X-Ray Computed Female
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FLANet: A multiscale temporal convolution and spatial-spectral attention network for EEG artifact removal with adversarial training.

Journal of neural engineering Feb 4, 2025
Denoising artifacts, such as noise from muscle or cardiac activity, is a crucial and ubiquitous concern in neurophysiological signal processing, particularly for enhancing the signal-to-noise ratio in electroencephalograph (EEG) analysis. Novel metho...
Deep Learning Electroencephalography Signal Processing, Computer-Assisted Attention Artifacts Signal-To-Noise Ratio Humans Neural Networks, Computer
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Synthetic data generation in motion analysis: A generative deep learning framework.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine Feb 4, 2025
Generative deep learning has emerged as a promising data augmentation technique in recent years. This approach becomes particularly valuable in areas such as motion analysis, where it is challenging to collect substantial amounts of data. The objecti...
Deep Learning Knee Joint Hip Joint Humans Biomechanical Phenomena Male Mechanical Phenomena Movement
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CQformer: Learning Dynamics Across Slices in Medical Image Segmentation.

IEEE transactions on medical imaging Feb 4, 2025
Prevalent studies on deep learning-based 3D medical image segmentation capture the continuous variation across 2D slices mainly via convolution, Transformer, inter-slice interaction, and time series models. In this work, via modeling this variation b...
Algorithms Databases, Factual Brain Humans Imaging, Three-Dimensional Magnetic Resonance Imaging Tomography, X-Ray Computed Deep Learning
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GobletNet: Wavelet-Based High-Frequency Fusion Network for Semantic Segmentation of Electron Microscopy Images.

IEEE transactions on medical imaging Feb 4, 2025
Semantic segmentation of electron microscopy (EM) images is crucial for nanoscale analysis. With the development of deep neural networks (DNNs), semantic segmentation of EM images has achieved remarkable success. However, current EM image segmentatio...
Wavelet Analysis Neural Networks, Computer Algorithms Deep Learning Image Processing, Computer-Assisted Semantics Microscopy, Electron Humans
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Integrating Eye Tracking With Grouped Fusion Networks for Semantic Segmentation on Mammogram Images.

IEEE transactions on medical imaging Feb 4, 2025
Medical image segmentation has seen great progress in recent years, largely due to the development of deep neural networks. However, unlike in computer vision, high-quality clinical data is relatively scarce, and the annotation process is often a bur...
Algorithms Female Breast Neoplasms Humans Neural Networks, Computer Mammography Breast Semantics Eye-Tracking Technology Deep Learning Image Processing, Computer-Assisted
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