discusses how X-ray images and CT (computerized tomography) scans can reveal much about the effects of the disease on a patient's lungs. However, the use of convolutional neural networks (CNN ...

A recent study from the University of California Los Angeles (UCLA) used deep neural networks to virtually stain microscopic images of unlabeled tissue. The research was published in Intelligent ...

"Neural networks and machine learning have a potential of improving the evaluation of breast symmetry in the field of Plastic ... with further advances in image detection capabilities and their ...

This paper proposes an end-to-end trained fully convolutional neural network model to process 3D image volumes. Unlike previous works ... 2018 as a part of the CMPT 880 Special Topics in AI: Medical ...

and medical image analysis. In the field of neuroscience, researchers often use neural networks to try to model the same kind of tasks that the brain performs, in hopes that the models could ...

The convolutional neural network (CNN) algorithm, known as LF-SynthSR, converts low-field-strength ... General Hospital and Harvard Medical School. Morphometry, the quantitative size and shape ...

A Convolutional Neural ... network to maintain consistent feature detection capabilities across the entire input image while minimizing memory requirements and processing overhead. Healthcare and ...

Traditional methods for image reconstruction require extensive manual labor and specialized knowledge. Now, researchers have developed a novel neural network model that can reconstruct these ...