AIMC Topic: Magnetic Resonance Imaging
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Interpretable machine learning and radiomics in hip MRI diagnostics: comparing ONFH and OA predictions to experts.
Frontiers in immunology
Jan 29, 2025
PURPOSE: Distinguishing between Osteonecrosis of the femoral head (ONFH) and Osteoarthritis (OA) can be subjective and vary between users with different backgrounds and expertise. This study aimed to construct and evaluate several Radiomics-based mac...
M2OCNN: Many-to-One Collaboration Neural Networks for simultaneously multi-modal medical image synthesis and fusion.
Computer methods and programs in biomedicine
Jan 28, 2025
BACKGROUND AND OBJECTIVE: Acquiring comprehensive information from multi-modal medical images remains a challenge in clinical diagnostics and treatment, due to complex inter-modal dependencies and missing modalities. While cross-modal medical image s...
Artificial intelligence for brain neuroanatomical segmentation in magnetic resonance imaging: A literature review.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jan 28, 2025
PURPOSE: This literature review aims to synthesise current research on the application of artificial intelligence (AI) for the segmentation of brain neuroanatomical structures in magnetic resonance imaging (MRI).
Dilated SE-DenseNet for brain tumor MRI classification.
Scientific reports
Jan 28, 2025
In the field of medical imaging, particularly MRI-based brain tumor classification, we propose an advanced convolutional neural network (CNN) leveraging the DenseNet-121 architecture, enhanced with dilated convolutional layers and Squeeze-and-Excitat...
Data- and Physics-Driven Deep Learning Based Reconstruction for Fast MRI: Fundamentals and Methodologies.
IEEE reviews in biomedical engineering
Jan 28, 2025
Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric, temporal and quantitative scans. This review elucidates recent advan...
Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions.
IEEE reviews in biomedical engineering
Jan 28, 2025
Breast cancer has reached the highest incidence rate worldwide among all malignancies since 2020. Breast imaging plays a significant role in early diagnosis and intervention to improve the outcome of breast cancer patients. In the past decade, deep l...
Identifying Primary Sites of Spinal Metastases: Expert-Derived Features vs. ResNet50 Model Using Nonenhanced MRI.
Journal of magnetic resonance imaging : JMRI
Jan 27, 2025
BACKGROUND: The spinal column is a frequent site for metastases, affecting over 30% of solid tumor patients. Identifying the primary tumor is essential for guiding clinical decisions but often requires resource-intensive diagnostics.
Integration of MRI radiomics and clinical data for preoperative prediction of vascular invasion in breast cancer: A deep learning approach.
Magnetic resonance imaging
Jan 27, 2025
BACKGROUND: Accurate preoperative prediction of vascular invasion in breast cancer is crucial for surgical planning and patient management. MRI radiomics has shown promise in enhancing diagnostic precision. This study aims to evaluate the effectivene...
Breast
Image Interpretation, Computer-Assisted
Preoperative Care
Diffusion Magnetic Resonance Imaging
Female
Contrast Media
Humans
Aged
Magnetic Resonance Imaging
Retrospective Studies
Adult
Neoplasm Invasiveness
Sensitivity and Specificity
Middle Aged
Breast Neoplasms
Deep Learning
Radiomics
Image Processing, Computer-Assisted
Semi-supervised Strong-Teacher Consistency Learning for few-shot cardiac MRI image segmentation.
Computer methods and programs in biomedicine
Jan 27, 2025
BACKGROUND AND OBJECTIVE: Cardiovascular disease is a leading cause of mortality worldwide. Automated analysis of heart structures in MRI is crucial for effective diagnostics. While supervised learning has advanced the field of medical image segmenta...
Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma.
Journal of translational medicine
Jan 27, 2025
BACKGROUND: Glioblastoma (GBM) is a highly aggressive brain tumor associated with a poor patient prognosis. The survival rate remains low despite standard therapies, highlighting the urgent need for novel treatment strategies. Advanced imaging techni...
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