AIMC Topic: Magnetic Resonance Imaging
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Generative AI for weakly supervised segmentation and downstream classification of brain tumors on MR images.
Scientific reports
Jul 1, 2025
Segmenting abnormalities is a leading problem in medical imaging. Using machine learning for segmentation generally requires manually annotated segmentations, demanding extensive time and resources from radiologists. We propose a weakly supervised ap...
Multi-modal and Multi-view Cervical Spondylosis Imaging Dataset.
Scientific data
Jul 1, 2025
Multi-modal and multi-view imaging is essential for diagnosis and assessment of cervical spondylosis. Deep learning has increasingly been developed to assist in diagnosis and assessment, which can help improve clinical management and provide new idea...
FPGA implementation of deep learning architecture for ankylosing spondylitis detection from MRI.
Scientific reports
Jul 1, 2025
Ankylosing Spondylitis (AS), commonly known as Bechterew's disease, is a complex, potentially disabling disease that develops slowly over time and progresses to radiographic sacroiliitis. The etiology of this disease is poorly understood, making it d...
Prediction of axillary lymph node metastasis in triple negative breast cancer using MRI radiomics and clinical features.
Scientific reports
Jul 1, 2025
To develop and validate a machine learning-based prediction model to predict axillary lymph node (ALN) metastasis in triple negative breast cancer (TNBC) patients using magnetic resonance imaging (MRI) and clinical characteristics. This retrospective...
A highly generalized federated learning algorithm for brain tumor segmentation.
Scientific reports
Jul 1, 2025
Brain image segmentation plays a pivotal role in modern healthcare by enabling precise diagnosis and treatment planning. Federated Learning (FL) enables collaborative model training across institutions while safeguarding sensitive patient data. The i...
Anterior cruciate ligament tear detection based on Res2Net modified by improved Lévy flight distribution.
Scientific reports
Jul 1, 2025
Anterior Cruciate Ligament (ACL) tears are common in sports and can provide noteworthy health issues. Therefore, accurately diagnosing of tears is important for the early and proper treatment. However, traditional diagnostic methods, such as clinical...
Spondyloarthritis Research and Treatment Network (SPARTAN) Clinical and Imaging Year in Review 2024.
Current rheumatology reports
Jul 1, 2025
PURPOSE OF REVIEW: Diagnostic delay remains a critical challenge in axial spondyloarthritis (axSpA). This review highlights key clinical and imaging research from 2024 that addresses this persistent issue, with a focus on the evolving roles of MRI, a...
CMT-FFNet: A CMT-based feature-fusion network for predicting TACE treatment response in hepatocellular carcinoma.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 30, 2025
Accurately and preoperatively predicting tumor response to transarterial chemoembolization (TACE) treatment is crucial for individualized treatment decision-making hepatocellular carcinoma (HCC). In this study, we propose a novel feature fusion netwo...
D2C-Morph: Brain regional segmentation based on unsupervised registration network with similarity analysis.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 30, 2025
Brain regional segmentation is an image-processing approach widely used in brain image analyses. Deep learning models that perform segmentation alone play an important role in medical fields such as automatic diagnosis and prognosis prediction. This ...
U-Net-based architecture with attention mechanisms and Bayesian Optimization for brain tumor segmentation using MR images.
Computers in biology and medicine
Jun 30, 2025
As technological innovation in computers has advanced, radiologists may now diagnose brain tumors (BT) with the use of artificial intelligence (AI). In the medical field, early disease identification enables further therapies, where the use of AI sys...
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