AIMC Topic: Diagnostic Imaging

Clear Filters Showing 381 to 390 of 1008 articles

Artificial Intelligence in the Imaging of Diffuse Lung Disease.

Radiologic clinics of North America
Diffuse lung diseases are a heterogeneous group of disorders that can be difficult to differentiate by imaging using traditional methods of evaluation. The overlap between various disorders results in difficulty when medical professionals attempt to ...

Cardiovascular Imaging in China: Yesterday, Today, and Tomorrow.

Journal of thoracic imaging
The high prevalence and mortality of cardiovascular diseases in China's large population has increased the use of cardiovascular imaging for the assessment of conditions in recent years. In this study, we review the past 20 years of cardiovascular im...

Fast, efficient, and accurate neuro-imaging denoising via supervised deep learning.

Nature communications
Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applie...

Advances in Deep-Learning-Based Sensing, Imaging, and Video Processing.

Sensors (Basel, Switzerland)
Deep learning techniques have shown their capabilities to discover knowledge from massive unstructured data, providing data-driven solutions for representation and decision making [...].

Comparison of Different Convolutional Neural Network Activation Functions and Methods for Building Ensembles for Small to Midsize Medical Data Sets.

Sensors (Basel, Switzerland)
CNNs and other deep learners are now state-of-the-art in medical imaging research. However, the small sample size of many medical data sets dampens performance and results in overfitting. In some medical areas, it is simply too labor-intensive and ex...

Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and meta-analysis.

Scientific reports
Machine learning (ML) algorithms are becoming increasingly pervasive in the domains of medical diagnostics and prognostication, afforded by complex deep learning architectures that overcome the limitations of manual feature extraction. In this system...

Dermoscopy and skin imaging light sources: a comparison and review of spectral power distribution and color consistency.

Journal of biomedical optics
SIGNIFICANCE: Dermoscopes incorporate light, polarizers, and optical magnification into a handheld tool that is commonly used by dermatologists to evaluate skin findings. Diagnostic accuracy is improved when dermoscopes are used, and some major artif...

Addressing fairness in artificial intelligence for medical imaging.

Nature communications
A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception. Here w...

Deep learning-based noise filtering toward millisecond order imaging by using scanning transmission electron microscopy.

Scientific reports
Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM's high affinity with various analytical options into account. As is well...

Computer-aided anatomy recognition in intrathoracic and -abdominal surgery: a systematic review.

Surgical endoscopy
BACKGROUND: Minimally invasive surgery is complex and associated with substantial learning curves. Computer-aided anatomy recognition, such as artificial intelligence-based algorithms, may improve anatomical orientation, prevent tissue injury, and im...