AIMC Topic: Diagnostic Imaging

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A deep learning framework for inference of single-trial neural population dynamics from calcium imaging with subframe temporal resolution.

Nature neuroscience Nov 24, 2022
In many areas of the brain, neural populations act as a coordinated network whose state is tied to behavior on a millisecond timescale. Two-photon (2p) calcium imaging is a powerful tool to probe such network-scale phenomena. However, estimating the ...
Population Dynamics Brain Calcium Deep Learning Diagnostic Imaging Mice Animals
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Determination of Wheat Heading Stage Using Convolutional Neural Networks on Multispectral UAV Imaging Data.

Computational intelligence and neuroscience Nov 24, 2022
The heading and flowering stages are crucial for wheat growth and should be used for fusarium head blight (FHB) and other plant prevention operations. Rapid and accurate monitoring of wheat growth in hilly areas is critical for determining plant prot...
Triticum Support Vector Machine Neural Networks, Computer Diagnostic Imaging
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An Orchestration Platform that Puts Radiologists in the Driver's Seat of AI Innovation: a Methodological Approach.

Journal of digital imaging Nov 23, 2022
Current AI-driven research in radiology requires resources and expertise that are often inaccessible to small and resource-limited labs. The clinicians who are able to participate in AI research are frequently well-funded, well-staffed, and either ha...
Radiology Diagnostic Imaging Radiologists Artificial Intelligence Humans Machine Learning
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RGBD Salient Object Detection, Based on Specific Object Imaging.

Sensors (Basel, Switzerland) Nov 19, 2022
RGBD salient object detection, based on the convolutional neural network, has achieved rapid development in recent years. However, existing models often focus on detecting salient object edges, instead of objects. Importantly, detecting objects can m...
Diagnostic Imaging Neural Networks, Computer
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Evaluation of Preprocessing Methods on Independent Medical Hyperspectral Databases to Improve Analysis.

Sensors (Basel, Switzerland) Nov 18, 2022
Currently, one of the most common causes of death worldwide is cancer. The development of innovative methods to support the early and accurate detection of cancers is required to increase the recovery rate of patients. Several studies have shown that...
Artificial Intelligence Diagnostic Imaging Humans Algorithms Brain Neoplasms Databases, Factual
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Elasticity imaging using physics-informed neural networks: Spatial discovery of elastic modulus and Poisson's ratio.

Acta biomaterialia Nov 17, 2022
Elasticity imaging is a technique that discovers the spatial distribution of mechanical properties of tissue using deformation and force measurements under various loading conditions. Given the complexity of this discovery, most existing methods appr...
Elastic Modulus Elasticity Physics Finite Element Analysis Diagnostic Imaging Stress, Mechanical Neural Networks, Computer Humans
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Mapping the Landscape of Care Providers' Quality Assurance Approaches for AI in Diagnostic Imaging.

Journal of digital imaging Nov 9, 2022
The discussion on artificial intelligence (AI) solutions in diagnostic imaging has matured in recent years. The potential value of AI adoption is well established, as are the potential risks associated. Much focus has, rightfully, been on regulatory ...
Humans Artificial Intelligence Radiology Diagnostic Imaging
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Artificial intelligence and automation in endoscopy and surgery.

Nature reviews. Gastroenterology & hepatology Nov 9, 2022
Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and...
Automation Artificial Intelligence Endoscopy, Gastrointestinal Diagnostic Imaging Endoscopy Humans
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Deep Learning for HDR Imaging: State-of-the-Art and Future Trends.

IEEE transactions on pattern analysis and machine intelligence Nov 7, 2022
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range of exposures, which is important in image processing, computer graphics, and computer vision. In recent years, there has been a significant advancement in HDR imag...
Algorithms Diagnostic Imaging Computer Graphics Image Processing, Computer-Assisted Deep Learning
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Deep label fusion: A generalizable hybrid multi-atlas and deep convolutional neural network for medical image segmentation.

Medical image analysis Nov 5, 2022
Deep convolutional neural networks (DCNN) achieve very high accuracy in segmenting various anatomical structures in medical images but often suffer from relatively poor generalizability. Multi-atlas segmentation (MAS), while less accurate than DCNN i...
Humans Neural Networks, Computer Diagnostic Imaging Image Processing, Computer-Assisted
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