AIMC Journal:
IEEE transactions on medical imaging

Showing 501 to 510 of 691 articles

Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet.

IEEE transactions on medical imaging Feb 27, 2019
Multi-parametric MRI (mp-MRI) is considered the best non-invasive imaging modality for diagnosing prostate cancer (PCa). However, mp-MRI for PCa diagnosis is currently limited by the qualitative or semi-quantitative interpretation criteria, leading t...
Male Prostatic Neoplasms Humans Neural Networks, Computer Neoplasm Grading Image Interpretation, Computer-Assisted Prostate Multiparametric Magnetic Resonance Imaging
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Image Synthesis in Multi-Contrast MRI With Conditional Generative Adversarial Networks.

IEEE transactions on medical imaging Feb 26, 2019
Acquiring images of the same anatomy with multiple different contrasts increases the diversity of diagnostic information available in an MR exam. Yet, the scan time limitations may prohibit the acquisition of certain contrasts, and some contrasts may...
Glioma Humans Magnetic Resonance Imaging Brain Neoplasms Neural Networks, Computer Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Brain
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A Machine Learning Approach for Classifying Ischemic Stroke Onset Time From Imaging.

IEEE transactions on medical imaging Feb 25, 2019
Current clinical practice relies on clinical history to determine the time since stroke (TSS) onset. Imaging-based determination of acute stroke onset time could provide critical information to clinicians in deciding stroke treatment options, such as...
Humans Algorithms Magnetic Resonance Imaging Brain Stroke Deep Learning Brain Ischemia
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Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography.

IEEE transactions on medical imaging Feb 22, 2019
Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis. Over the past decades, the automation of this task has been the subject of intense research. In this paper, we evaluate how far...
Image Processing, Computer-Assisted Heart Humans Algorithms Echocardiography Deep Learning Databases, Factual
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Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation.

IEEE transactions on medical imaging Feb 18, 2019
Glaucoma is a leading cause of irreversible blindness. Accurate segmentation of the optic disc (OD) and optic cup (OC) from fundus images is beneficial to glaucoma screening and diagnosis. Recently, convolutional neural networks demonstrate promising...
Optic Disk Diagnostic Techniques, Ophthalmological Glaucoma Databases, Factual Fundus Oculi Image Interpretation, Computer-Assisted ROC Curve Humans Neural Networks, Computer
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Generative Adversarial Networks for Facilitating Stain-Independent Supervised and Unsupervised Segmentation: A Study on Kidney Histology.

IEEE transactions on medical imaging Feb 14, 2019
A major challenge in the field of segmentation in digital pathology is given by the high effort for manual data annotations in combination with many sources introducing variability in the image domain. This requires methods that are able to cope with...
Humans Data Curation Kidney Histocytochemistry Machine Learning Image Processing, Computer-Assisted
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Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting.

IEEE transactions on medical imaging Feb 13, 2019
Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that can simultaneously measure multiple important tissue properties of human body. Although MRF has demonstrated improved scan efficiency as compared to conventional techniq...
Magnetic Resonance Imaging Time Factors Image Processing, Computer-Assisted Algorithms Brain Deep Learning Humans
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Attention to Lesion: Lesion-Aware Convolutional Neural Network for Retinal Optical Coherence Tomography Image Classification.

IEEE transactions on medical imaging Feb 8, 2019
Automatic and accurate classification of retinal optical coherence tomography (OCT) images is essential to assist ophthalmologist in the diagnosis and grading of macular diseases. Clinically, ophthalmologists usually diagnose macular diseases accordi...
Humans Neural Networks, Computer Retina Retinal Diseases Databases, Factual Tomography, Optical Coherence
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Learning a Probabilistic Model for Diffeomorphic Registration.

IEEE transactions on medical imaging Feb 4, 2019
We propose to learn a low-dimensional probabilistic deformation model from data which can be used for the registration and the analysis of deformations. The latent variable model maps similar deformations close to each other in an encoding space. It ...
Humans Models, Statistical Algorithms Deep Learning Heart Image Processing, Computer-Assisted Magnetic Resonance Imaging, Cine
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Robust Single-Shot T Mapping via Multiple Overlapping-Echo Acquisition and Deep Neural Network.

IEEE transactions on medical imaging Jan 31, 2019
Quantitative magnetic resonance imaging (MRI) is of great value to both clinical diagnosis and scientific research. However, most MRI experiments remain qualitative, especially dynamic MRI, because repeated sampling with variable weighting parameter ...
Deep Learning Brain Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Computer Simulation Artifacts Algorithms Phantoms, Imaging
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