AIMC Topic:
Image Interpretation, Computer-Assisted

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Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRI.

Magnetic resonance in medicine Aug 7, 2019
PURPOSE: This prospective clinical study assesses the feasibility of training a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion-weighted MRI (DW-MRI) data and evaluates its performance.
Adult Male Middle Aged Deep Learning Image Processing, Computer-Assisted Kidney Liver Bayes Theorem Algorithms Pancreas Prospective Studies Spleen Computer Simulation Humans Least-Squares Analysis Diffusion Magnetic Resonance Imaging Reproducibility of Results Motion Image Interpretation, Computer-Assisted
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Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey.

Artificial intelligence in medicine Aug 7, 2019
Diabetic retinopathy (DR) results in vision loss if not treated early. A computer-aided diagnosis (CAD) system based on retinal fundus images is an efficient and effective method for early DR diagnosis and assisting experts. A computer-aided diagnosi...
Machine Learning Biomarkers Diagnosis, Computer-Assisted Deep Learning Fundus Oculi Humans Retina Diabetic Retinopathy Image Interpretation, Computer-Assisted
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A Deep Learning Model to Triage Screening Mammograms: A Simulation Study.

Radiology Aug 6, 2019
Background Recent deep learning (DL) approaches have shown promise in improving sensitivity but have not addressed limitations in radiologist specificity or efficiency. Purpose To develop a DL model to triage a portion of mammograms as cancer free, i...
Computer Simulation Retrospective Studies Female Aged Aged, 80 and over Deep Learning Triage Adult Cohort Studies Registries Breast Neoplasms Mammography Breast Middle Aged Image Interpretation, Computer-Assisted Humans
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Automatic cataract grading methods based on deep learning.

Computer methods and programs in biomedicine Aug 5, 2019
BACKGROUND AND OBJECTIVE: The shortage of ophthalmologists in rural areas in China causes a lot of cataract patients not getting timely diagnosis and effective treatment. We develop an algorithm and platform to automatically diagnose and grade catara...
Deep Learning Support Vector Machine Cataract Fundus Oculi Image Interpretation, Computer-Assisted Humans Automation
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Current applications and future directions of deep learning in musculoskeletal radiology.

Skeletal radiology Aug 4, 2019
Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number of musculoskeletal applications of deep learning, w...
Humans Neural Networks, Computer Deep Learning Musculoskeletal System Diagnostic Imaging Radiology Image Interpretation, Computer-Assisted Musculoskeletal Diseases
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Deep-learning based detection of gastric precancerous conditions.

Gut Aug 2, 2019
Image Interpretation, Computer-Assisted Precancerous Conditions Gastroscopy Gastritis, Atrophic Humans Aged, 80 and over Middle Aged Algorithms Adult Deep Learning Female Stomach Neoplasms Aged Chronic Disease Male
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Advances in computer-aided medical systems and clinical measurement.

Computer assisted surgery (Abingdon, England) Aug 2, 2019
Electroencephalography Surgery, Computer-Assisted Image Interpretation, Computer-Assisted Phantoms, Imaging Humans Artificial Intelligence Computer-Aided Design Diagnostic Imaging
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Learning to Quantify Emphysema Extent: What Labels Do We Need?

IEEE journal of biomedical and health informatics Aug 1, 2019
Accurate assessment of pulmonary emphysema is crucial to assess disease severity and subtype, to monitor disease progression, and to predict lung cancer risk. However, visual assessment is time-consuming and subject to substantial inter-rater variabi...
Image Interpretation, Computer-Assisted Disease Progression Lung Pulmonary Emphysema Humans Machine Learning Algorithms Tomography, X-Ray Computed Female Male Middle Aged
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Measurement-oriented deep-learning workflow for improved segmentation of myelin and axons in high-resolution images of human cerebral white matter.

Journal of neuroscience methods Aug 1, 2019
BACKGROUND: Standard segmentation of high-contrast electron micrographs (EM) identifies myelin accurately but does not translate easily into measurements of individual axons and their myelin, even in cross-sections of parallel fibers. We describe aut...
Humans Deep Learning Workflow Image Interpretation, Computer-Assisted Microscopy, Electron Autopsy White Matter Myelin Sheath Cerebrum Axons
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Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding.

NeuroImage Jul 31, 2019
White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factor...
White Matter Middle Aged Age Factors Image Interpretation, Computer-Assisted Humans Aged Magnetic Resonance Imaging Pattern Recognition, Automated Machine Learning Aged, 80 and over Brain Diseases Female Male Neuroimaging Aging
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