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Showing 7498-7518 of 14,525 articles

Artificial Intelligence for Optimization and Interpretation of PET/CT and PET/MR Images.

Artificial intelligence (AI) has recently attracted much attention for its potential use in healthca...

Nov 2020 33509370

Artificial Intelligence for Response Evaluation With PET/CT.

Positron emission tomography (PET)/computed tomography (CT) are nuclear diagnostic imaging modalitie...

Nov 2020 33509372

Progressive multifocal leukoencephalopathy lesion and brain parenchymal segmentation from MRI using serial deep convolutional neural networks.

Progressive multifocal leukoencephalopathy (PML) is a rare opportunistic brain infection caused by t...

Nov 2020 33395989

Generating anthropomorphic phantoms using fully unsupervised deformable image registration with convolutional neural networks.

PURPOSE: Computerized phantoms have been widely used in nuclear medicine imaging for imaging system ...

Nov 2020 33078422

A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT.

This project aimed to develop and evaluate a fast and fully-automated deep-learning method applying ...

Nov 2020 33168895

Diagnostic accuracy of deep-learning with anomaly detection for a small amount of imbalanced data: discriminating malignant parotid tumors in MRI.

We hypothesized that, in discrimination between benign and malignant parotid gland tumors, high diag...

Nov 2020 33168936

Image Segmentation of the Ventricular Septum in Fetal Cardiac Ultrasound Videos Based on Deep Learning Using Time-Series Information.

Image segmentation is the pixel-by-pixel detection of objects, which is the most challenging but inf...

Nov 2020 33171658

Multimodal magnetic resonance imaging correlates of motor outcome after stroke using machine learning.

This study applied machine learning regression to predict motor function after stroke based on multi...

Nov 2020 33166636

Intravenous Line Phase-Wrap Artifact at Bilateral Axial 3-T Breast MRI: Identification, Analysis, and Solution.

PURPOSE: To understand and remove the source of a phase-wrap artifact produced by residual contrast ...

Nov 2020 33778747

Capsules for biomedical image segmentation.

Our work expands the use of capsule networks to the task of object segmentation for the first time i...

Nov 2020 33246227

A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography.

PURPOSE: Deep learning can be used for improving the performance of computer-aided detection (CADe) ...

Nov 2020 33150471

Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.

Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke...

Nov 2020 32604080

Deep learning networks on chronic liver disease assessment with fine-tuning of shear wave elastography image sequences.

Chronic liver disease (CLD) is currently one of the major causes of death worldwide. If not treated,...

Nov 2020 32998480

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography.

Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVI...

Nov 2020 33154542

Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images.

Cross-modality medical image synthesis between magnetic resonance (MR) images and computed tomograph...

Nov 2020 33204701

Obtaining PET/CT images from non-attenuation corrected PET images in a single PET system using Wasserstein generative adversarial networks.

Positron emission tomography (PET) imaging plays an indispensable role in early disease detection an...

Nov 2020 32663812

Browse Categories

Artificial Intelligence for Optimization and Interpretation of PET/CT and PET/MR Images.

Artificial Intelligence for Response Evaluation With PET/CT.

Progressive multifocal leukoencephalopathy lesion and brain parenchymal segmentation from MRI using serial deep convolutional neural networks.

Generating anthropomorphic phantoms using fully unsupervised deformable image registration with convolutional neural networks.

A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT.

Diagnostic accuracy of deep-learning with anomaly detection for a small amount of imbalanced data: discriminating malignant parotid tumors in MRI.

Image Segmentation of the Ventricular Septum in Fetal Cardiac Ultrasound Videos Based on Deep Learning Using Time-Series Information.

Multimodal magnetic resonance imaging correlates of motor outcome after stroke using machine learning.

Intravenous Line Phase-Wrap Artifact at Bilateral Axial 3-T Breast MRI: Identification, Analysis, and Solution.

Capsules for biomedical image segmentation.

A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography.

Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.

Deep learning networks on chronic liver disease assessment with fine-tuning of shear wave elastography image sequences.

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography.

Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images.

Alzheimer's diagnosis using deep learning in segmenting and classifying 3D brain MR images.

Reliability of robotic transcranial magnetic stimulation motor mapping.

Improving Breast Cancer Detection Accuracy of Mammography with the Concurrent Use of an Artificial Intelligence Tool.

Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.

Deep Learning for Detecting Cerebral Aneurysms with CT Angiography.

Obtaining PET/CT images from non-attenuation corrected PET images in a single PET system using Wasserstein generative adversarial networks.

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