AIMC Topic: Magnetic Resonance Imaging
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Deep learning radiomics based on MRI for differentiating tongue cancer T - staging.
BMC cancer
Aug 22, 2025
OBJECTIVE: To develop a deep learning-based MRI model for predicting tongue cancer T-stage.
Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study.
Translational psychiatry
Aug 22, 2025
Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it still remains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain...
Memory-enhanced and multi-domain learning-based deep unrolling network for medical image reconstruction.
Physics in medicine and biology
Aug 21, 2025
. Reconstructing high-quality images from corrupted measurements remains a fundamental challenge in medical imaging. Recently, deep unrolling (DUN) methods have emerged as a promising solution, combining the interpretability of traditional iterative ...
Predicting knee osteoarthritis progression using neural network with longitudinal MRI radiomics, and biochemical biomarkers: A modeling study.
PLoS medicine
Aug 21, 2025
BACKGROUND: Knee osteoarthritis (KOA) worsens both structurally and symptomatically, yet no model predicts KOA progression using Magnetic Resonance Image (MRI) radiomics and biomarkers. This study aimed to develop and test the longitudinal Load-Beari...
Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.
BMC cancer
Aug 20, 2025
BACKGROUND: Renal cell carcinoma (RCC) is a prevalent malignancy with highly variable outcomes. MicroRNA-15a (miR-15a) has emerged as a promising prognostic biomarker in RCC, linked to angiogenesis, apoptosis, and proliferation. Radiogenomics integra...
An effective flowchart for multimodal brain tumor binary classification with ranked 3D texture features.
Scientific reports
Aug 20, 2025
Brain tumors have complex structures, and their shape, density, and size can vary widely. Consequently, their accurate classification, which involves identifying features that best describe the tumor data, is challenging. Using classical 2D texture f...
A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation.
Scientific data
Aug 20, 2025
Multi-modality magnetic resonance imaging(MRI) data facilitate the early diagnosis, tumor segmentation, and disease staging in the management of nasopharyngeal carcinoma (NPC). The lack of publicly available, comprehensive datasets limits advancement...
Improving risk stratification of PI-RADS 3 + 1 lesions of the peripheral zone: expert lexicon of terms, multi-reader performance and contribution of artificial intelligence.
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 19, 2025
BACKGROUND: According to PI-RADS v2.1, peripheral PI-RADS 3 lesions are upgraded to PI-RADS 4 if dynamic contrast-enhanced MRI is positive (3+1 lesions), however those lesions are radiologically challenging. We aimed to define criteria by expert cons...
MRI-derived quantification of hepatic vessel-to-volume ratios in chronic liver disease using a deep learning approach.
European radiology experimental
Aug 12, 2025
BACKGROUND: We aimed to quantify hepatic vessel volumes across chronic liver disease stages and healthy controls using deep learning-based magnetic resonance imaging (MRI) analysis, and assess correlations with biomarkers for liver (dys)function and ...
Current imaging applications, radiomics, and machine learning modalities of CNS demyelinating disorders and its mimickers.
Journal of neurology
Aug 12, 2025
Distinguishing among neuroinflammatory demyelinating diseases of the central nervous system can present a significant diagnostic challenge due to substantial overlap in clinical presentations and imaging features. Collaboration between specialists, n...
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