AIMC Journal:
IEEE transactions on medical imaging

Showing 431 to 440 of 687 articles

On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality Assessment.

IEEE transactions on medical imaging Dec 13, 2019
Uncertainty of labels in clinical data resulting from intra-observer variability can have direct impact on the reliability of assessments made by deep neural networks. In this paper, we propose a method for modelling such uncertainty in the context o...
Observer Variation Humans Uncertainty Neural Networks, Computer Reproducibility of Results Echocardiography
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EMS-Net: A Deep Learning Method for Autodetecting Epileptic Magnetoencephalography Spikes.

IEEE transactions on medical imaging Dec 10, 2019
Epilepsy is a neurological disorder characterized by sudden and unpredictable epileptic seizures, which incurs significant negative impacts on patients' physical, psychological and social health. A practical approach to assist with the clinical asses...
Seizures Humans Electroencephalography Magnetoencephalography Deep Learning Epilepsy
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Progressively Trained Convolutional Neural Networks for Deformable Image Registration.

IEEE transactions on medical imaging Nov 15, 2019
Deep learning-based methods for deformable image registration are attractive alternatives to conventional registration methods because of their short registration times. However, these methods often fail to estimate larger displacements in complex de...
Neural Networks, Computer Tomography, X-Ray Computed Humans
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Dilated Residual Learning With Skip Connections for Real-Time Denoising of Laser Speckle Imaging of Blood Flow in a Log-Transformed Domain.

IEEE transactions on medical imaging Nov 14, 2019
Laser speckle contrast imaging (LSCI) is a wide-field and noncontact imaging technology for mapping blood flow. Although the denoising method based on block-matching and three-dimensional transform-domain collaborative filtering (BM3D) was proposed t...
Signal-To-Noise Ratio Neural Networks, Computer Lasers
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Deep Learning Analysis of Coronary Arteries in Cardiac CT Angiography for Detection of Patients Requiring Invasive Coronary Angiography.

IEEE transactions on medical imaging Nov 12, 2019
In patients with obstructive coronary artery disease, the functional significance of a coronary artery stenosis needs to be determined to guide treatment. This is typically established through fractional flow reserve (FFR) measurement, performed duri...
Humans Retrospective Studies Coronary Angiography Coronary Artery Disease Deep Learning Predictive Value of Tests Computed Tomography Angiography Coronary Vessels Fractional Flow Reserve, Myocardial
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A 3D Probabilistic Deep Learning System for Detection and Diagnosis of Lung Cancer Using Low-Dose CT Scans.

IEEE transactions on medical imaging Oct 29, 2019
We introduce a new computer aided detection and diagnosis system for lung cancer screening with low-dose CT scans that produces meaningful probability assessments. Our system is based entirely on 3D convolutional neural networks and achieves state-of...
Imaging, Three-Dimensional Tomography, X-Ray Computed Humans Early Detection of Cancer Deep Learning Lung Neoplasms
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A Multi-Organ Nucleus Segmentation Challenge.

IEEE transactions on medical imaging Oct 23, 2019
Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology datasets. We summarize the results of MoNuSeg 2018 Challenge whose objective was to develop ge...
Cell Nucleus Neural Networks, Computer Image Processing, Computer-Assisted Humans
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Induced-Current Learning Method for Nonlinear Reconstructions in Electrical Impedance Tomography.

IEEE transactions on medical imaging Oct 22, 2019
Electrical impedance tomography (EIT) is an attractive technique that aims to reconstruct the unknown electrical property in a domain from the surface electrical measurements. In this work, the induced-current learning method (ICLM) is proposed to so...
Image Processing, Computer-Assisted Electric Impedance Tomography, X-Ray Computed Tomography Neural Networks, Computer
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MoDL-MUSSELS: Model-Based Deep Learning for Multishot Sensitivity-Encoded Diffusion MRI.

IEEE transactions on medical imaging Oct 9, 2019
We introduce a model-based deep learning architecture termed MoDL-MUSSELS for the correction of phase errors in multishot diffusion-weighted echo-planar MR images. The proposed algorithm is a generalization of the existing MUSSELS algorithm with simi...
Brain Deep Learning Image Processing, Computer-Assisted Connectome Humans Algorithms Diffusion Magnetic Resonance Imaging
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Visual Correspondences for Unsupervised Domain Adaptation on Electron Microscopy Images.

IEEE transactions on medical imaging Oct 9, 2019
We present an Unsupervised Domain Adaptation strategy to compensate for domain shifts on Electron Microscopy volumes. Our method aggregates visual correspondences-motifs that are visually similar across different acquisitions-to infer changes on the ...
Microscopy, Electron Mitochondria Mice Animals Algorithms Unsupervised Machine Learning Image Processing, Computer-Assisted Brain
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