AIMC Topic: Diagnostic Imaging

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High-quality photoacoustic image reconstruction based on deep convolutional neural network: towards intra-operative photoacoustic imaging.

Biomedical physics & engineering express Jun 12, 2020
The use of intra-operative imaging system as an intervention solution to provide more accurate localization of complicated structures has become a necessity during the neurosurgery. However, due to the limitations of conventional imaging systems, hig...
Deep Learning Time Factors Image Processing, Computer-Assisted Brain Animals Signal-To-Noise Ratio Phantoms, Imaging Photoacoustic Techniques Diagnostic Imaging Artifacts Mice Neural Networks, Computer Algorithms Humans
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Photoacoustic Imaging to Track Magnetic-manipulated Micro-Robots in Deep Tissue.

Sensors (Basel, Switzerland) May 15, 2020
The next generation of intelligent robotic systems has been envisioned as micro-scale mobile and externally controllable robots. Visualization of such small size microrobots to track their motion in nontransparent medium such as human tissue remains ...
Phantoms, Imaging Photoacoustic Techniques Humans Ultrasonography Diagnostic Imaging Magnetics Robotics
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An Improved Pulse-Coupled Neural Network Model for Pansharpening.

Sensors (Basel, Switzerland) May 12, 2020
Pulse-coupled neural network (PCNN) and its modified models are suitable for dealing with multi-focus and medical image fusion tasks. Unfortunately, PCNNs are difficult to directly apply to multispectral image fusion, especially when the spectral fid...
Visual Perception Algorithms Humans Image Processing, Computer-Assisted Neural Networks, Computer Diagnostic Imaging
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Diagnostic accuracy of diabetic retinopathy grading by an artificial intelligence-enabled algorithm compared with a human standard for wide-field true-colour confocal scanning and standard digital retinal images.

The British journal of ophthalmology May 6, 2020
BACKGROUND: Photographic diabetic retinopathy screening requires labour-intensive grading of retinal images by humans. Automated retinal image analysis software (ARIAS) could provide an alternative to human grading. We compare the performance of an A...
Male Middle Aged Image Processing, Computer-Assisted Sensitivity and Specificity Cross-Sectional Studies Retina Diagnostic Tests, Routine False Positive Reactions Predictive Value of Tests Diagnostic Imaging Microscopy, Confocal Algorithms Female Aged Adult Reproducibility of Results Humans Diabetic Retinopathy Artificial Intelligence Reference Standards Slit Lamp Microscopy
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Opening the black box of machine learning in radiology: can the proximity of annotated cases be a way?

European radiology experimental May 5, 2020
Machine learning (ML) and deep learning (DL) systems, currently employed in medical image analysis, are data-driven models often considered as black boxes. However, improved transparency is needed to translate automated decision-making to clinical pr...
Diagnostic Imaging Humans Image Interpretation, Computer-Assisted Machine Learning Decision Support Techniques
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Medical Imaging and Privacy in the Era of Artificial Intelligence: Myth, Fallacy, and the Future.

Journal of the American College of Radiology : JACR Apr 28, 2020
Artificial Intelligence Forecasting Diagnostic Imaging Privacy Radiography
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Proceedings from the First Global Artificial Intelligence in Gastroenterology and Endoscopy Summit.

Gastrointestinal endoscopy Apr 25, 2020
BACKGROUND AND AIMS: Artificial intelligence (AI), specifically deep learning, offers the potential to enhance the field of GI endoscopy in areas ranging from lesion detection and classification to quality metrics and documentation. Progress in this ...
Machine Learning Humans Endoscopy Diagnostic Imaging Artificial Intelligence Gastroenterology
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Less is More: Intelligent Intensive Care for SARS-CoV-2 Based on the Imaging Data.

Journal of medical imaging and radiation sciences Apr 18, 2020
Pneumonia, Viral Coronavirus Infections Critical Care Betacoronavirus Artificial Intelligence SARS-CoV-2 Pandemics Diagnostic Imaging COVID-19 Humans
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Surgical spectral imaging.

Medical image analysis Apr 13, 2020
Recent technological developments have resulted in the availability of miniaturised spectral imaging sensors capable of operating in the multi- (MSI) and hyperspectral imaging (HSI) regimes. Simultaneous advances in image-processing techniques and ar...
Machine Learning Humans Image Processing, Computer-Assisted Artificial Intelligence Diagnostic Imaging
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Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation.

Medical image analysis Apr 3, 2020
The medical imaging literature has witnessed remarkable progress in high-performing segmentation models based on convolutional neural networks. Despite the new performance highs, the recent advanced segmentation models still require large, representa...
Humans Deep Learning Diagnostic Imaging Neural Networks, Computer
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