AIMC Topic: Image Processing, Computer-Assisted
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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
Mar 15, 2025
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
Mar 15, 2025
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...
A deep learning approach to multi-fiber parameter estimation and uncertainty quantification in diffusion MRI.
Medical image analysis
Mar 14, 2025
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)
Mar 14, 2025
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
Mar 14, 2025
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
Mar 14, 2025
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
Mar 14, 2025
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...
Deep learning-based automated segmentation of cardiac real-time MRI in non-human primates.
Computers in biology and medicine
Mar 13, 2025
Advanced imaging techniques, like magnetic resonance imaging (MRI), have revolutionised cardiovascular disease diagnosis and monitoring in humans and animal models. Real-time (RT) MRI, which can capture a single slice during each consecutive heartbea...
Deep learning in nuclear medicine: from imaging to therapy.
Annals of nuclear medicine
Mar 13, 2025
BACKGROUND: Deep learning, a leading technology in artificial intelligence (AI), has shown remarkable potential in revolutionizing nuclear medicine.
MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning.
Genome medicine
Mar 13, 2025
Spatially resolved transcriptomics (SRT) simultaneously measure spatial location, histology images, and transcriptional profiles of cells or regions in undissociated tissues. Integrative analysis of multi-modal SRT data holds immense potential for un...
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