AIMC Journal:
Medical image analysis

Showing 361 to 370 of 684 articles

Brain graph super-resolution using adversarial graph neural network with application to functional brain connectivity.

Medical image analysis Apr 21, 2021
Brain image analysis has advanced substantially in recent years with the proliferation of neuroimaging datasets acquired at different resolutions. While research on brain image super-resolution has undergone a rapid development in the recent years, b...
Neural Networks, Computer Brain Humans Image Processing, Computer-Assisted Neuroimaging
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Diverse data augmentation for learning image segmentation with cross-modality annotations.

Medical image analysis Apr 20, 2021
The dearth of annotated data is a major hurdle in building reliable image segmentation models. Manual annotation of medical images is tedious, time-consuming, and significantly variable across imaging modalities. The need for annotation can be amelio...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Humans
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Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.

Medical image analysis Apr 15, 2021
The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital breast tomosynthesis (DBT), a pseudo-3D technique, is now commonly us...
Radiation Dosage Breast Density Mammography Deep Learning Humans Breast Breast Neoplasms Female
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A survey on active learning and human-in-the-loop deep learning for medical image analysis.

Medical image analysis Apr 9, 2021
Fully automatic deep learning has become the state-of-the-art technique for many tasks including image acquisition, analysis and interpretation, and for the extraction of clinically useful information for computer-aided detection, diagnosis, treatmen...
Humans Image Processing, Computer-Assisted Deep Learning
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Consolidated domain adaptive detection and localization framework for cross-device colonoscopic images.

Medical image analysis Apr 6, 2021
Automatic polyp detection has been proven to be crucial in improving the diagnosis accuracy and reducing colorectal cancer mortality during the precancerous stage. However, the performance of deep neural networks may degrade severely when being deplo...
Software Neural Networks, Computer
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Two-stage deep learning for accelerated 3D time-of-flight MRA without matched training data.

Medical image analysis Apr 5, 2021
Time-of-flight magnetic resonance angiography (TOF-MRA) is one of the most widely used non-contrast MR imaging methods to visualize blood vessels, but due to the 3-D volume acquisition highly accelerated acquisition is necessary. Accordingly, high qu...
Image Processing, Computer-Assisted Magnetic Resonance Angiography Magnetic Resonance Imaging Deep Learning
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Longitudinal self-supervised learning.

Medical image analysis Apr 4, 2021
Machine learning analysis of longitudinal neuroimaging data is typically based on supervised learning, which requires large number of ground-truth labels to be informative. As ground-truth labels are often missing or expensive to obtain in neuroscien...
Humans Magnetic Resonance Imaging Supervised Machine Learning Brain Machine Learning
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Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review.

Medical image analysis Apr 3, 2021
The relatively recent reintroduction of deep learning has been a revolutionary force in the interpretation of diagnostic imaging studies. However, the technology used to acquire those images is undergoing a revolution itself at the very same time. Di...
Breast Neoplasms Deep Learning Female Humans Breast Mammography Early Detection of Cancer
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CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification.

Medical image analysis Apr 1, 2021
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem. We de...
Humans COVID-19 Pandemics Triage SARS-CoV-2 Deep Learning Tomography, X-Ray Computed
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BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset.

Medical image analysis Mar 31, 2021
In this work we design an end-to-end deep learning architecture for predicting, on Chest X-rays images (CXR), a multi-regional score conveying the degree of lung compromise in COVID-19 patients. Such semi-quantitative scoring system, namely Brixia sc...
Deep Learning X-Rays SARS-CoV-2 Humans COVID-19 Radiography, Thoracic
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