AIMC Journal:
IEEE transactions on medical imaging

Showing 251 to 260 of 687 articles

Harmonizing Pathological and Normal Pixels for Pseudo-Healthy Synthesis.

IEEE transactions on medical imaging Aug 31, 2022
Synthesizing a subject-specific pathology-free image from a pathological image is valuable for algorithm development and clinical practice. In recent years, several approaches based on the Generative Adversarial Network (GAN) have achieved promising ...
Algorithms Neural Networks, Computer Image Processing, Computer-Assisted
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Unsupervised Histological Image Registration Using Structural Feature Guided Convolutional Neural Network.

IEEE transactions on medical imaging Aug 31, 2022
Registration of multiple stained images is a fundamental task in histological image analysis. In supervised methods, obtaining ground-truth data with known correspondences is laborious and time-consuming. Thus, unsupervised methods are expected. Unsu...
Neural Networks, Computer Image Processing, Computer-Assisted Algorithms
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Deformation-Compensated Learning for Image Reconstruction Without Ground Truth.

IEEE transactions on medical imaging Aug 31, 2022
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets. Recent work on Noise2Noise (N2N) has shown the potential of using multiple noisy measurements of the same obje...
Neural Networks, Computer Magnetic Resonance Imaging Image Processing, Computer-Assisted
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Global and Local Feature Reconstruction for Medical Image Segmentation.

IEEE transactions on medical imaging Aug 31, 2022
Learning how to capture long-range dependencies and restore spatial information of down-sampled feature maps are the basis of the encoder-decoder structure networks in medical image segmentation. U-Net based methods use feature fusion to alleviate th...
Image Processing, Computer-Assisted Semantics Neural Networks, Computer
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Deep Relation Learning for Regression and Its Application to Brain Age Estimation.

IEEE transactions on medical imaging Aug 31, 2022
Most deep learning models for temporal regression directly output the estimation based on single input images, ignoring the relationships between different images. In this paper, we propose deep relation learning for regression, aiming to learn diffe...
Child Seizures Child, Preschool Brain Aged Infant, Newborn Neural Networks, Computer Algorithms Infant Humans Middle Aged Young Adult Aged, 80 and over Adult Adolescent Deep Learning
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Multi-Modal Graph Learning for Disease Prediction.

IEEE transactions on medical imaging Aug 31, 2022
Benefiting from the powerful expressive capability of graphs, graph-based approaches have been popularly applied to handle multi-modal medical data and achieved impressive performance in various biomedical applications. For disease prediction tasks, ...
Machine Learning Humans
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Deep Learning-Based Photoacoustic Imaging of Vascular Network Through Thick Porous Media.

IEEE transactions on medical imaging Aug 1, 2022
Photoacoustic imaging is a promising approach used to realize in vivo transcranial cerebral vascular imaging. However, the strong attenuation and distortion of the photoacoustic wave caused by the thick porous skull greatly affect the imaging quality...
Porosity Photoacoustic Techniques Image Processing, Computer-Assisted Neural Networks, Computer Deep Learning Algorithms
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DeepGrading: Deep Learning Grading of Corneal Nerve Tortuosity.

IEEE transactions on medical imaging Aug 1, 2022
Accurate estimation and quantification of the corneal nerve fiber tortuosity in corneal confocal microscopy (CCM) is of great importance for disease understanding and clinical decision-making. However, the grading of corneal nerve tortuosity remains ...
Cornea Microscopy, Confocal Deep Learning Nerve Fibers
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3D Segmentation Guided Style-Based Generative Adversarial Networks for PET Synthesis.

IEEE transactions on medical imaging Aug 1, 2022
Potential radioactive hazards in full-dose positron emission tomography (PET) imaging remain a concern, whereas the quality of low-dose images is never desirable for clinical use. So it is of great interest to translate low-dose PET images into full-...
Radiation Dosage Neural Networks, Computer Radiation Injuries Positron-Emission Tomography Image Processing, Computer-Assisted Deep Learning
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Noise Reduction in CT Using Learned Wavelet-Frame Shrinkage Networks.

IEEE transactions on medical imaging Aug 1, 2022
Encoding-decoding (ED) CNNs have demonstrated state-of-the-art performance for noise reduction over the past years. This has triggered the pursuit of better understanding the inner workings of such architectures, which has led to the theory of deep c...
Image Processing, Computer-Assisted Signal-To-Noise Ratio Tomography, X-Ray Computed Neural Networks, Computer
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