AIMC Topic: Humans

Clear Filters Showing 57421 to 57430 of 95995 articles

Comparison of iterative parametric and indirect deep learning-based reconstruction methods in highly undersampled DCE-MR Imaging of the breast.

Medical physics
PURPOSE: To compare the performance of iterative direct and indirect parametric reconstruction methods with indirect deep learning-based reconstruction methods in estimating tracer-kinetic parameters from highly undersampled DCE-MR Imaging breast dat...

Image-level detection of arterial occlusions in 4D-CTA of acute stroke patients using deep learning.

Medical image analysis
The triage of acute stroke patients is increasingly dependent on four-dimensional CTA (4D-CTA) imaging. In this work, we present a convolutional neural network (CNN) for image-level detection of intracranial anterior circulation artery occlusions in ...

fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations.

NeuroImage
Deep-learning methods based on deep neural networks (DNNs) have recently been successfully utilized in the analysis of neuroimaging data. A convolutional neural network (CNN) is a type of DNN that employs a convolution kernel that covers a local area...

Artificial intelligence technology applications in the pathologic diagnosis of the gastrointestinal tract.

Future oncology (London, England)
Artificial intelligence (AI) is a complex technology with a steady flow of new applications, including in the pathology laboratory. Applications of AI in pathology are scarce but increasing; they are based on complex software-based machine learning w...

Quantitative Modeling of Spasticity for Clinical Assessment, Treatment and Rehabilitation.

Sensors (Basel, Switzerland)
Spasticity, a common symptom in patients with upper motor neuron lesions, reduces the ability of a person to freely move their limbs by generating unwanted reflexes. Spasticity can interfere with rehabilitation programs and cause pain, muscle atrophy...

Development and validation of a model to predict survival in colorectal cancer using a gradient-boosted machine.

Gut
OBJECTIVE: The success of treatment planning relies critically on our ability to predict the potential benefit of a therapy. In colorectal cancer (CRC), several nomograms are available to predict different outcomes based on the use of tumour specific...

Classification of parotid gland tumors by using multimodal MRI and deep learning.

NMR in biomedicine
Various MRI sequences have shown their potential to discriminate parotid gland tumors, including but not limited to T -weighted, postcontrast T -weighted, and diffusion-weighted images. In this study, we present a fully automatic system for the diagn...