AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Prior knowledge-based multi-task learning network for pulmonary nodule classification.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 16, 2025
The morphological characteristics of pulmonary nodule, also known as the attributes, are crucial for classification of benign and malignant nodules. In clinical, radiologists usually conduct a comprehensive analysis of correlations between different ...
Machine-learning tool for classifying pulmonary hypertension via expert reader-provided CT features: An educational resource for non-dedicated radiologists.
European journal of radiology
Feb 15, 2025
PURPOSE: Pulmonary hypertension (PH) is a complex disease classified into five groups (I-V) by the European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines. Chest contrast-enhanced computed tomography (CECT) is crucial in the ...
Development and application of AI assisted automatic reconstruction of axial lumbar disc CT images and diagnosis of lumbar disc herniation.
European journal of radiology
Feb 13, 2025
RATIONALE AND OBJECTIVES: To evaluate the value of artificial intelligence (AI) assisted diagnostic system in reconstructing axial lumbar disc CT images and diagnosing lumbar disc herniation.
Artificial Intelligence Model for Detection of Colorectal Cancer on Routine Abdominopelvic CT Examinations: A Training and External-Testing Study.
AJR. American journal of roentgenology
Feb 12, 2025
Radiologists are prone to missing some colorectal cancers (CRCs) on routine abdominopelvic CT examinations that are in fact detectable on the images. The purpose of this study was to develop an artificial intelligence (AI) model to detect CRC on ro...
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 ...
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...
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...
Middle Aged
Deep Learning
Diagnosis, Differential
Carcinoma, Renal Cell
Radiographic Image Interpretation, Computer-Assisted
Kidney Neoplasms
Sensitivity and Specificity
Radiomics
Male
Aged
Aged, 80 and over
Adult
Humans
Female
Reproducibility of Results
Retrospective Studies
Tomography, X-Ray Computed
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...
PlaqueViT: a vision transformer model for fully automatic vessel and plaque segmentation in coronary computed tomography angiography.
European radiology
Feb 5, 2025
OBJECTIVES: To develop and evaluate a deep learning model for segmentation of the coronary artery vessels and coronary plaques in coronary computed tomography angiography (CCTA).
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 ...
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