AIMC Journal:
Medical image analysis

Showing 291 to 300 of 684 articles

Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning.

Medical image analysis Apr 8, 2022
Due to the difficulty in accessing a large amount of labeled data, semi-supervised learning is becoming an attractive solution in medical image segmentation. To make use of unlabeled data, current popular semi-supervised methods (e.g., temporal ensem...
Humans Image Processing, Computer-Assisted Uncertainty Supervised Machine Learning
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FOD-Net: A deep learning method for fiber orientation distribution angular super resolution.

Medical image analysis Apr 6, 2022
Mapping the human connectome using fiber-tracking permits the study of brain connectivity and yields new insights into neuroscience. However, reliable connectome reconstruction using diffusion magnetic resonance imaging (dMRI) data acquired by widely...
Humans Brain Connectome Deep Learning Image Processing, Computer-Assisted Diffusion Magnetic Resonance Imaging
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Recent advances and clinical applications of deep learning in medical image analysis.

Medical image analysis Apr 4, 2022
Deep learning has received extensive research interest in developing new medical image processing algorithms, and deep learning based models have been remarkably successful in a variety of medical imaging tasks to support disease detection and diagno...
Deep Learning Algorithms Diagnostic Imaging Supervised Machine Learning Image Processing, Computer-Assisted Humans
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Rendezvous: Attention mechanisms for the recognition of surgical action triplets in endoscopic videos.

Medical image analysis Mar 26, 2022
Out of all existing frameworks for surgical workflow analysis in endoscopic videos, action triplet recognition stands out as the only one aiming to provide truly fine-grained and comprehensive information on surgical activities. This information, pre...
Neural Networks, Computer Laparoscopy Humans Semantics Workflow
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Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge.

Medical image analysis Mar 24, 2022
A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed 10 min aft...
Magnetic Resonance Imaging Myocardial Infarction Humans Contrast Media Deep Learning Myocardium
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Image quality assessment for machine learning tasks using meta-reinforcement learning.

Medical image analysis Mar 21, 2022
In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is performed using machine learning algorithms, such as a neural-network-bas...
Ultrasonography Humans Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Machine Learning Male
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Instance importance-Aware graph convolutional network for 3D medical diagnosis.

Medical image analysis Mar 18, 2022
Automatic diagnosis of 3D medical data is a significant goal of intelligent healthcare. By exploiting the abundant pathological information of 3D data, human experts and algorithms can provide accurate predictions for patients. Considering the high c...
Humans Algorithms Neural Networks, Computer Learning
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Towards bi-directional skip connections in encoder-decoder architectures and beyond.

Medical image analysis Mar 16, 2022
U-Net, as an encoder-decoder architecture with forward skip connections, has achieved promising results in various medical image analysis tasks. Many recent approaches have also extended U-Net with more complex building blocks, which typically increa...
Neural Networks, Computer Humans Image Processing, Computer-Assisted Algorithms
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Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification.

Medical image analysis Mar 12, 2022
Morphological abnormalities of the femoroacetabular (hip) joint are among the most common human musculoskeletal disorders and often develop asymptomatically at early easily treatable stages. In this paper, we propose an automated framework for landma...
Magnetic Resonance Imaging Hip Joint Neural Networks, Computer Learning Humans
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An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data.

Medical image analysis Mar 2, 2022
Functional magnetic resonance imaging (fMRI) as a promising tool to investigate psychotic disorders can be decomposed into useful imaging features such as time courses (TCs) of independent components (ICs) and functional network connectivity (FNC) ca...
Brain Deep Learning Neural Networks, Computer Schizophrenia Magnetic Resonance Imaging Humans
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