AIMC Topic:
Magnetic Resonance Imaging
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Deep Learning Reconstruction of Accelerated MRI: False-Positive Cartilage Delamination Inserted in MRI Arthrography Under Traction.
Topics in magnetic resonance imaging : TMRI
Jul 12, 2024
OBJECTIVES: The radiological imaging industry is developing and starting to offer a range of novel artificial intelligence software solutions for clinical radiology. Deep learning reconstruction of magnetic resonance imaging data seems to allow for t...
Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare.
Scientific reports
Jul 12, 2024
AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases...
Improving brain atrophy quantification with deep learning from automated labels using tissue similarity priors.
Computers in biology and medicine
Jul 10, 2024
Brain atrophy measurements derived from magnetic resonance imaging (MRI) are a promising marker for the diagnosis and prognosis of neurodegenerative pathologies such as Alzheimer's disease or multiple sclerosis. However, its use in individualized ass...
CapNet: An Automatic Attention-Based with Mixer Model for Cardiovascular Magnetic Resonance Image Segmentation.
Journal of imaging informatics in medicine
Jul 9, 2024
Deep neural networks have shown excellent performance in medical image segmentation, especially for cardiac images. Transformer-based models, though having advantages over convolutional neural networks due to the ability of long-range dependence lear...
ScribSD+: Scribble-supervised medical image segmentation based on simultaneous multi-scale knowledge distillation and class-wise contrastive regularization.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 9, 2024
Despite that deep learning has achieved state-of-the-art performance for automatic medical image segmentation, it often requires a large amount of pixel-level manual annotations for training. Obtaining these high-quality annotations is time-consuming...
Synthetic CT generation for pelvic cases based on deep learning in multi-center datasets.
Radiation oncology (London, England)
Jul 9, 2024
BACKGROUND AND PURPOSE: To investigate the feasibility of synthesizing computed tomography (CT) images from magnetic resonance (MR) images in multi-center datasets using generative adversarial networks (GANs) for rectal cancer MR-only radiotherapy.
Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI.
Scientific reports
Jul 9, 2024
A three-dimensional convolutional neural network model was developed to classify the severity of chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) imaging. Sev...
AI-assisted Segmentation Tool for Brain Tumor MR Image Analysis.
Journal of imaging informatics in medicine
Jul 8, 2024
TumorPrism3D software was developed to segment brain tumors with a straightforward and user-friendly graphical interface applied to two- and three-dimensional brain magnetic resonance (MR) images. The MR images of 185 patients (103 males, 82 females)...
CFINet: Cross-Modality MRI Feature Interaction Network for Pseudoprogression Prediction of Glioblastoma.
Journal of computational biology : a journal of computational molecular cell biology
Jul 8, 2024
Pseudoprogression (PSP) is a related reaction of glioblastoma treatment, and misdiagnosis can lead to unnecessary intervention. Magnetic resonance imaging (MRI) provides cross-modality images for PSP prediction studies. However, how to effectively us...
Multimodal Deep Learning-based Radiomics Approach for Predicting Surgical Outcomes in Patients with Cervical Ossification of the Posterior Longitudinal Ligament.
Spine
Jul 8, 2024
STUDY DESIGN: A retrospective analysis.
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