AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Double-mix pseudo-label framework: enhancing semi-supervised segmentation on category-imbalanced CT volumes.

International journal of computer assisted radiology and surgery Feb 11, 2025
PURPOSE: Deep-learning-based supervised CT segmentation relies on fully and densely labeled data, the labeling process of which is time-consuming. In this study, our proposed method aims to improve segmentation performance on CT volumes with limited ...
Radiographic Image Interpretation, Computer-Assisted Heart Defects, Congenital Tomography, X-Ray Computed Deep Learning Humans
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Automatic Joint Lesion Detection by enhancing local feature interaction.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 10, 2025
Recently, deep learning models have demonstrated impressive performance in Automatic Joint Lesion Detection (AJLD), yet balancing accuracy and efficiency remains a significant challenge. This paper focuses on achieving end-to-end lesion detection whi...
Arthritis Joints Deep Learning Radiographic Image Interpretation, Computer-Assisted Humans Algorithms
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Integration of radiomic and deep features to reliably differentiate benign renal lesions from renal cell carcinoma.

European journal of radiology Feb 7, 2025
PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial for optimized management, particularly for small renal lesions (≤4 cm in diameter). This study aimed to integrate clinical data, radiomic features, a...
Reproducibility of Results Aged Adult Sensitivity and Specificity Aged, 80 and over Kidney Neoplasms Retrospective Studies Carcinoma, Renal Cell Tomography, X-Ray Computed Middle Aged Radiographic Image Interpretation, Computer-Assisted Female Deep Learning Humans Radiomics Diagnosis, Differential Male
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TQGDNet: Coronary artery calcium deposit detection on computed tomography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 6, 2025
Coronary artery disease (CAD) continues to be a leading global cause of cardiovascular related mortality. The scoring of coronary artery calcium (CAC) using computer tomography (CT) images is a diagnostic instrument for evaluating the risk of asympto...
Vascular Calcification Humans Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Neural Networks, Computer Coronary Vessels Tomography, X-Ray Computed
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Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection.

Scientific reports Feb 5, 2025
Employing two standard mammography views is crucial for radiologists, providing comprehensive insights for reliable clinical evaluations. This study introduces paired mammogram view based-network(PMVnet), a novel algorithm designed to enhance breast ...
Deep Learning Mammography Radiographic Image Interpretation, Computer-Assisted Female Breast Neoplasms Humans Algorithms
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Facing Differences of Similarity: Intra- and Inter-Correlation Unsupervised Learning for Chest X-Ray Anomaly Detection.

IEEE transactions on medical imaging Feb 4, 2025
Anomaly detection can significantly aid doctors in interpreting chest X-rays. The commonly used strategy involves utilizing the pre-trained network to extract features from normal data to establish feature representations. However, when a pre-trained...
Humans Unsupervised Machine Learning Radiographic Image Interpretation, Computer-Assisted Databases, Factual Algorithms Lung Radiography, Thoracic
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Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture.

Academic radiology Feb 3, 2025
RATIONALE AND OBJECTIVES: This research aimed to develop a combined model based on proximal femur attenuation values and radiomics features at routine CT to predict hip fragility fracture using machine learning methods.
Tomography, X-Ray Computed Female Risk Factors Humans Machine Learning Radiomics Risk Assessment Male Radiographic Image Interpretation, Computer-Assisted Hip Fractures Aged Middle Aged Aged, 80 and over
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Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer.

BMC medical imaging Feb 3, 2025
Liver cancer detection is critically important in the discipline of biomedical image testing and diagnosis. Researchers have explored numerous machine learning (ML) techniques and deep learning (DL) approaches aimed at the automated recognition of li...
Liver Neoplasms Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Deep Learning Humans Neural Networks, Computer
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Practical X-ray gastric cancer diagnostic support using refined stochastic data augmentation and hard boundary box training.

Artificial intelligence in medicine Feb 1, 2025
Endoscopy is widely used to diagnose gastric cancer and has a high diagnostic performance, but it must be performed by a physician, which limits the number of people who can be diagnosed. In contrast, gastric X-rays can be taken by radiographers, thu...
Deep Learning Radiographic Image Interpretation, Computer-Assisted Stochastic Processes Humans Machine Learning Stomach Neoplasms
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Adjacent point aided vertebral landmark detection and Cobb angle measurement for automated AIS diagnosis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 30, 2025
Adolescent Idiopathic Scoliosis (AIS) is a prevalent structural deformity disease of human spine, and accurate assessment of spinal anatomical parameters is essential for clinical diagnosis and treatment planning. In recent years, significant progres...
Radiographic Image Interpretation, Computer-Assisted Deep Learning Scoliosis Spine Humans Adolescent Anatomic Landmarks Algorithms
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