AIMC Topic: Image Interpretation, Computer-Assisted
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Enhanced glioma tumor detection and segmentation using modified deep learning with edge fusion and frequency features.
Scientific reports
Feb 26, 2025
Computer-aided automatic brain tumor detection is crucial for timely diagnosis and treatment, especially in regions with limited access to medical expertise. However, existing methods often overlook edge pixel information during tumor segmentation, l...
Comparison of the impact of rectal susceptibility artifacts in prostate magnetic resonance imaging on subjective evaluation and deep learning: a two-center retrospective study.
BMC medical imaging
Feb 25, 2025
BACKGROUND: To compare the influence of rectal susceptibility artifacts on the subjective evaluation and deep learning (DL) in prostate cancer (PCa) diagnosis.
MSTNet: Multi-scale spatial-aware transformer with multi-instance learning for diabetic retinopathy classification.
Medical image analysis
Feb 24, 2025
Diabetic retinopathy (DR), the leading cause of vision loss among diabetic adults worldwide, underscores the importance of early detection and timely treatment using fundus images to prevent vision loss. However, existing deep learning methods strugg...
Deep transfer learning radiomics for distinguishing sinonasal malignancies: a preliminary MRI study.
Future oncology (London, England)
Feb 24, 2025
PURPOSE: This study aimed to assess the diagnostic accuracy of combining MRI hand-crafted (HC) radiomics features with deep transfer learning (DTL) in identifying sinonasal squamous cell carcinoma (SCC), adenoid cystic carcinoma (ACC), and non-Hodgki...
MERIT: Multi-view evidential learning for reliable and interpretable liver fibrosis staging.
Medical image analysis
Feb 22, 2025
Accurate staging of liver fibrosis from magnetic resonance imaging (MRI) is crucial in clinical practice. While conventional methods often focus on a specific sub-region, multi-view learning captures more information by analyzing multiple patches sim...
Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
Feb 21, 2025
BACKGROUND: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties in image interpretation. The AVVIGO IVUS Automated Lesion Assessment (ALA) software, which uses mac...
Aged
Male
Stents
Middle Aged
Image Interpretation, Computer-Assisted
Predictive Value of Tests
Observer Variation
Machine Learning
Ultrasonography, Interventional
Automation
Severity of Illness Index
Retrospective Studies
Percutaneous Coronary Intervention
Treatment Outcome
Female
Coronary Artery Disease
Coronary Vessels
Reproducibility of Results
Prosthesis Design
Humans
Deep learning models for differentiating three sinonasal malignancies using multi-sequence MRI.
BMC medical imaging
Feb 21, 2025
PURPOSE: To develop MRI-based deep learning (DL) models for distinguishing sinonasal squamous cell carcinoma (SCC), adenoid cystic carcinoma (ACC) and olfactory neuroblastoma (ONB) and to evaluate whether the DL models could improve the diagnostic pe...
Generalizable deep neural networks for image quality classification of cervical images.
Scientific reports
Feb 21, 2025
Successful translation of artificial intelligence (AI) models into clinical practice, across clinical domains, is frequently hindered by the lack of image quality control. Diagnostic models are often trained on images with no denotation of image qual...
TRUSWorthy: toward clinically applicable deep learning for confident detection of prostate cancer in micro-ultrasound.
International journal of computer assisted radiology and surgery
Feb 20, 2025
PURPOSE: While deep learning methods have shown great promise in improving the effectiveness of prostate cancer (PCa) diagnosis by detecting suspicious lesions from trans-rectal ultrasound (TRUS), they must overcome multiple simultaneous challenges. ...
A multi-task self-supervised approach for mass detection in automated breast ultrasound using double attention recurrent residual U-Net.
Computers in biology and medicine
Feb 20, 2025
Breast cancer is the most common and lethal cancer among women worldwide. Early detection using medical imaging technologies can significantly improve treatment outcomes. Automated breast ultrasound, known as ABUS, offers more advantages compared to ...
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