AIMC Topic: Diagnostic Imaging

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Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks.

European radiology experimental
A huge amount of imaging data is becoming available worldwide and an incredible range of possible improvements can be provided by artificial intelligence algorithms in clinical care for diagnosis and decision support. In this context, it has become e...

Maintenance and Management Technology of Medical Imaging Equipment Based on Deep Learning.

Contrast media & molecular imaging
Medical equipment maintenance in modern hospital management is an emerging marginal discipline which is one of the important branches of hospital management with the dual function of management and technology. The good or bad management of medical eq...

Biomedical Microscopic Imaging in Computational Intelligence Using Deep Learning Ensemble Convolution Learning-Based Feature Extraction and Classification.

Computational intelligence and neuroscience
Microscopy image analysis gives quantitative support for enhancing the characterizations of various diseases, including breast cancer, lung cancer, and brain tumors. As a result, it is crucial in computer-assisted diagnosis and prognosis. Understandi...

Current challenges of implementing artificial intelligence in medical imaging.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The idea of using artificial intelligence (AI) in medical practice has gained vast interest due to its potential to revolutionise healthcare systems. However, only some AI algorithms are utilised due to systems' uncertainties, besides the never-endin...

Deep learning for improving the spatial resolution of magnetic particle imaging.

Physics in medicine and biology
Magnetic particle imaging (MPI) is a new medical, non-destructive, imaging method for visualizing the spatial distribution of superparamagnetic iron oxide nanoparticles. In MPI, spatial resolution is an important indicator of efficiency; traditional ...

Improving Medical Images Classification With Label Noise Using Dual-Uncertainty Estimation.

IEEE transactions on medical imaging
Deep neural networks are known to be data-driven and label noise can have a marked impact on model performance. Recent studies have shown great robustness to classic image recognition even under a high noisy rate. In medical applications, learning fr...

A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation.

IEEE transactions on medical imaging
In the last years, deep learning has dramatically improved the performances in a variety of medical image analysis applications. Among different types of deep learning models, convolutional neural networks have been among the most successful and they...

Collaborative Robotic Wire + Arc Additive Manufacture and Sensor-Enabled In-Process Ultrasonic Non-Destructive Evaluation.

Sensors (Basel, Switzerland)
The demand for cost-efficient manufacturing of complex metal components has driven research for metal Additive Manufacturing (AM) such as Wire + Arc Additive Manufacturing (WAAM). WAAM enables automated, time- and material-efficient manufacturing of ...

Virtual reality in cardiac interventions-New tools or new toys?

Journal of cardiac surgery
Improvementsin medical imaging and a steady increase in computing power are leading to new possibilities in the field of cardiovascular interventions. Interventions can be planned in advance in greater detail, even to the point of simulating procedur...

Surgical Selection of T1 Stage Renal Tumor Resection Based on Imaging MAP Score under Smart Medical Care.

Computational intelligence and neuroscience
Smart medical uses the medical information platform and the current technological means to enable the process of sharing information between medical staff and medical equipment. The combination of current technology and the medical field has become t...