AIMC Journal:
Medical image analysis

Showing 401 to 410 of 684 articles

Fully automated left atrium segmentation from anatomical cine long-axis MRI sequences using deep convolutional neural network with unscented Kalman filter.

Medical image analysis Nov 26, 2020
This study proposes a fully automated approach for the left atrial segmentation from routine cine long-axis cardiac magnetic resonance image sequences using deep convolutional neural networks and Bayesian filtering. The proposed approach consists of ...
Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging Retrospective Studies Humans Bayes Theorem Heart Atria
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Hypergraph learning for identification of COVID-19 with CT imaging.

Medical image analysis Nov 26, 2020
The coronavirus disease, named COVID-19, has become the largest global public health crisis since it started in early 2020. CT imaging has been used as a complementary tool to assist early screening, especially for the rapid identification of COVID-1...
Pneumonia, Viral Datasets as Topic Community-Acquired Infections SARS-CoV-2 Diagnosis, Computer-Assisted Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted COVID-19 China Humans Tomography, X-Ray Computed Machine Learning
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COVID-AL: The diagnosis of COVID-19 with deep active learning.

Medical image analysis Nov 26, 2020
The efficient diagnosis of COVID-19 plays a key role in preventing the spread of this disease. The computer-aided diagnosis with deep learning methods can perform automatic detection of COVID-19 using CT scans. However, large scale annotation of CT s...
Pneumonia, Viral Deep Learning Datasets as Topic COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Diagnosis, Computer-Assisted Humans
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Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer.

Medical image analysis Nov 21, 2020
We apply for the first-time interpretable deep learning methods simultaneously to the most common skin cancers (basal cell carcinoma, squamous cell carcinoma and intraepidermal carcinoma) in a histological setting. As these three cancer types constit...
Diagnosis, Computer-Assisted Deep Learning Skin Neoplasms Carcinoma, Squamous Cell Humans Algorithms
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Test-time adaptable neural networks for robust medical image segmentation.

Medical image analysis Nov 19, 2020
Convolutional Neural Networks (CNNs) work very well for supervised learning problems when the training dataset is representative of the variations expected to be encountered at test time. In medical image segmentation, this premise is violated when t...
Image Processing, Computer-Assisted Brain Prostate Humans Male Magnetic Resonance Imaging Neural Networks, Computer
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Learning to segment images with classification labels.

Medical image analysis Nov 19, 2020
Two of the most common tasks in medical imaging are classification and segmentation. Either task requires labeled data annotated by experts, which is scarce and expensive to collect. Annotating data for segmentation is generally considered to be more...
Breast Neoplasms Deep Learning Humans Female
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Cascaded convolutional networks for automatic cephalometric landmark detection.

Medical image analysis Nov 18, 2020
Cephalometric analysis is a fundamental examination which is widely used in orthodontic diagnosis and treatment planning. Its key step is to detect the anatomical landmarks in lateral cephalograms, which is time-consuming in traditional manual way. T...
Face Reproducibility of Results Radiography Cephalometry Neural Networks, Computer
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A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification.

Medical image analysis Nov 17, 2020
The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular ...
Arteries Retinal Vessels Humans Algorithms Machine Learning Retina
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Dynamic MRI reconstruction with end-to-end motion-guided network.

Medical image analysis Nov 13, 2020
Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is informative and important to understand motion mechanisms of body regions. Modeling such information into the MRI reconstruction process produces temporally coh...
Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Heart Neural Networks, Computer Algorithms Motion Artifacts
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A deep learning framework for quality assessment and restoration in video endoscopy.

Medical image analysis Nov 13, 2020
Endoscopy is a routine imaging technique used for both diagnosis and minimally invasive surgical treatment. Artifacts such as motion blur, bubbles, specular reflections, floating objects and pixel saturation impede the visual interpretation and the a...
Deep Learning Image Processing, Computer-Assisted Artifacts Neural Networks, Computer Endoscopy
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