AIMC Journal:
IEEE transactions on medical imaging

Showing 231 to 240 of 687 articles

Using Simulated Training Data of Voxel-Level Generative Models to Improve 3D Neuron Reconstruction.

IEEE transactions on medical imaging Dec 2, 2022
Reconstructing neuron morphologies from fluorescence microscope images plays a critical role in neuroscience studies. It relies on image segmentation to produce initial masks either for further processing or final results to represent neuronal morpho...
Neural Networks, Computer Imaging, Three-Dimensional Image Processing, Computer-Assisted Neurons Microscopy
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Deep Learning-Powered Bessel-Beam Multiparametric Photoacoustic Microscopy.

IEEE transactions on medical imaging Dec 2, 2022
Enabling simultaneous and high-resolution quantification of the total concentration of hemoglobin ( [Formula: see text]), oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF), multi-parametric photoacoustic microscopy (PAM) has emerge...
Brain Animals Deep Learning Mice Hemoglobins Microscopy Spectrum Analysis Photoacoustic Techniques
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Contrastive and Selective Hidden Embeddings for Medical Image Segmentation.

IEEE transactions on medical imaging Oct 27, 2022
Medical image segmentation is fundamental and essential for the analysis of medical images. Although prevalent success has been achieved by convolutional neural networks (CNN), challenges are encountered in the domain of medical image analysis by two...
Neural Networks, Computer Image Processing, Computer-Assisted
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Dual Adversarial Attention Mechanism for Unsupervised Domain Adaptive Medical Image Segmentation.

IEEE transactions on medical imaging Oct 27, 2022
Domain adaptation techniques have been demonstrated to be effective in addressing label deficiency challenges in medical image segmentation. However, conventional domain adaptation based approaches often concentrate on matching global marginal distri...
Neural Networks, Computer Image Processing, Computer-Assisted
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CX-DaGAN: Domain Adaptation for Pneumonia Diagnosis on a Small Chest X-Ray Dataset.

IEEE transactions on medical imaging Oct 27, 2022
Recent advances in deep learning led to several algorithms for the accurate diagnosis of pneumonia from chest X-rays. However, these models require large training medical datasets, which are sparse, isolated, and generally private. Furthermore, these...
Humans Neural Networks, Computer Deep Learning Pneumonia X-Rays Nicardipine
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Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans.

IEEE transactions on medical imaging Oct 27, 2022
Accurately segmenting teeth and identifying the corresponding anatomical landmarks on dental mesh models are essential in computer-aided orthodontic treatment. Manually performing these two tasks is time-consuming, tedious, and, more importantly, hig...
Humans Machine Learning Deep Learning Image Processing, Computer-Assisted Surgical Mesh Tooth
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Benchmarking of Deep Architectures for Segmentation of Medical Images.

IEEE transactions on medical imaging Oct 27, 2022
In recent years, there were many suggestions regarding modifications of the well-known U-Net architecture in order to improve its performance. The central motivation of this work is to provide a fair comparison of U-Net and its five extensions using ...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Benchmarking
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Deep-Learning-Based Electrical Noise Removal Enables High Spectral Optoacoustic Contrast in Deep Tissue.

IEEE transactions on medical imaging Oct 27, 2022
Image contrast in multispectral optoacoustic tomography (MSOT) can be severely reduced by electrical noise and interference in the acquired optoacoustic signals. Previously employed signal processing techniques have proven insufficient to remove the ...
Humans Algorithms Deep Learning Image Processing, Computer-Assisted Signal-To-Noise Ratio Photoacoustic Techniques
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Exploring Intra- and Inter-Video Relation for Surgical Semantic Scene Segmentation.

IEEE transactions on medical imaging Oct 27, 2022
Automatic surgical scene segmentation is fundamental for facilitating cognitive intelligence in the modern operating theatre. Previous works rely on conventional aggregation modules (e.g., dilated convolution, convolutional LSTM), which only make use...
Neural Networks, Computer Endoscopy Semantics
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Semi-Supervised Neuron Segmentation via Reinforced Consistency Learning.

IEEE transactions on medical imaging Oct 27, 2022
Emerging deep learning-based methods have enabled great progress in automatic neuron segmentation from Electron Microscopy (EM) volumes. However, the success of existing methods is heavily reliant upon a large number of annotations that are often exp...
Image Processing, Computer-Assisted Supervised Machine Learning Neurons
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