AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 1041 to 1050 of 10288 articles

Light scattering imaging modal expansion cytometry for label-free single-cell analysis with deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Single-cell imaging plays a key role in various fields, including drug development, disease diagnosis, and personalized medicine. To obtain multi-modal information from a single-cell image, especially for label-free cells, t...

The impact of training image quality with a novel protocol on artificial intelligence-based LGE-MRI image segmentation for potential atrial fibrillation management.

Computer methods and programs in biomedicine
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting up to 2 % of the population. Catheter ablation is a promising treatment for AF, particularly for paroxysmal AF patients, but it often has high recurrence rates. Dev...

MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image Deformations.

Medical image analysis
Geometric transformations have been widely used to augment the size of training images. Existing methods often assume a unimodal distribution of the underlying transformations between images, which limits their power when data with multimodal distrib...

HADCN: a hierarchical ascending densely connected network for enhanced medical image segmentation.

Medical & biological engineering & computing
Medical image segmentation is a key component in computer-aided diagnostic technology. In the past few years, the U-shaped architecture-based hierarchical model has become the mainstream approach, which however often fails to provide accurate results...

Quantitative multislice and jointly optimized rapid CEST for in vivo whole-brain imaging.

Magnetic resonance in medicine
PURPOSE: To develop a quantitative multislice chemical exchange saturation transfer (CEST) schedule optimization and pulse sequence that reduces the loss of sensitivity inherent to multislice sequences.

A deep learning approach to multi-fiber parameter estimation and uncertainty quantification in diffusion MRI.

Medical image analysis
Diffusion MRI (dMRI) is the primary imaging modality used to study brain microstructure in vivo. Reliable and computationally efficient parameter inference for common dMRI biophysical models is a challenging inverse problem, due to factors such as va...

Adaptive Vectorial Restoration from Dynamic Speckle Patterns Through Biological Scattering Media Based on Deep Learning.

Sensors (Basel, Switzerland)
Imaging technologies based on vector optical fields hold significant potential in the biomedical field, particularly for non-invasive scattering imaging of anisotropic biological tissues. However, the dynamic and anisotropic nature of biological tiss...

Structured hashing with deep learning for modality, organ, and disease content sensitive medical image retrieval.

Scientific reports
Evidence-based medicine is the preferred procedure among clinicians for treating patients. Content-based medical image retrieval (CBMIR) is widely used to extract evidence from a large archive of medical images. Developing effective CBMIR systems for...

Comparative analysis of deep learning architectures for breast region segmentation with a novel breast boundary proposal.

Scientific reports
Segmentation of the breast region in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for the automatic measurement of breast density and the quantitative analysis of imaging findings. This study aims to compare various dee...

Alternate encoder and dual decoder CNN-Transformer networks for medical image segmentation.

Scientific reports
Accurately extracting lesions from medical images is a fundamental but challenging problem in medical image analysis. In recent years, methods based on convolutional neural networks and Transformer have achieved great success in the medical image seg...