AIMC Topic: Magnetic Resonance Imaging
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Accelerating veterinary low field MRI acquisitions using the deep learning based denoising solution HawkAI.
Scientific reports
Feb 18, 2025
Magnetic resonance imaging (MRI) has changed veterinary diagnosis but its long-sequence time can be problematic, especially because animals need to be sedated during the exam. Unfortunately, shorter scan times implies a fall in overall image quality ...
Brain tumor segmentation and classification using MRI: Modified segnet model and hybrid deep learning architecture with improved texture features.
Computational biology and chemistry
Feb 17, 2025
Brain tumors are quickly overtaking all other causes of death worldwide. The failure to perform a timely diagnosis is the main cause of increasing the death rate. Traditional methods of brain tumor diagnosis heavily rely on the expertise of radiologi...
FusionNet: Dual input feature fusion network with ensemble based filter feature selection for enhanced brain tumor classification.
Brain research
Feb 17, 2025
Brain tumors pose a significant threat to human health, require a precise and quick diagnosis for effective treatment. However, achieving high diagnostic accuracy with traditional methods remains challenging due to the complex nature of brain tumors....
Multicenter study on predicting postoperative upper limb muscle strength improvement in cervical spinal cord injury patients using radiomics and deep learning.
Scientific reports
Feb 17, 2025
Cervical spinal cord injury is often catastrophic, frequently leading to irreversible impairment. MRI has become the gold standard for evaluating spinal cord injuries (SCI). Our study aimed to assess the accuracy of a radiomics approach, based on mac...
Dense convolution-based attention network for Alzheimer's disease classification.
Scientific reports
Feb 17, 2025
Recently, deep learning-based medical image classification models have made substantial advancements. However, many existing models prioritize performance at the cost of efficiency, limiting their practicality in clinical use. Traditional Convolution...
Stacked CNN-based multichannel attention networks for Alzheimer disease detection.
Scientific reports
Feb 17, 2025
Alzheimer's Disease (AD) is a progressive condition of a neurological brain disorder recognized by symptoms such as dementia, memory loss, alterations in behaviour, and impaired reasoning abilities. Recently, many researchers have been working to dev...
Multi-label segmentation of carpal bones in MRI using expansion transfer learning.
Physics in medicine and biology
Feb 17, 2025
The purpose of this study was to develop a robust deep learning approach trained with a smallMRI dataset for multi-label segmentation of all eight carpal bones for therapy planning and wrist dynamic analysis.A small dataset of 15 3.0-T MRI scans from...
Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma.
Cancer imaging : the official publication of the International Cancer Imaging Society
Feb 16, 2025
BACKGROUND: Immunotherapy has revolutionized the treatment landscape for head and neck squamous cell carcinoma (HNSCC) and PD-L1 combined positivity score (CPS) scoring is recommended as a biomarker for immunotherapy. Therefore, this study aimed to d...
Z-SSMNet: Zonal-aware Self-supervised Mesh Network for prostate cancer detection and diagnosis with Bi-parametric MRI.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 15, 2025
Bi-parametric magnetic resonance imaging (bpMRI) has become a pivotal modality in the detection and diagnosis of clinically significant prostate cancer (csPCa). Developing AI-based systems to identify csPCa using bpMRI can transform prostate cancer (...
Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline.
Neural networks : the official journal of the International Neural Network Society
Feb 15, 2025
While numerous studies strive to exploit the complementary potential of MRI and PET using learning-based methods, the effective fusion of the two modalities remains a tricky problem due to their inherently distinctive properties. In addition, current...
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