AIMC Topic: Tomography, X-Ray Computed

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Deep learning model for measuring the sagittal Cobb angle on cervical spine computed tomography.

BMC medical imaging
PURPOSES: To develop a deep learning (DL) model to measure the sagittal Cobb angle of the cervical spine on computed tomography (CT).

CT analysis of aortic calcifications to predict abdominal aortic aneurysm rupture.

European radiology
BACKGROUND: Abdominal aortic aneurysm (AAA) rupture prediction based on sex and diameter could be improved. The goal was to assess whether aortic calcification distribution could better predict AAA rupture through machine learning and LASSO regressio...

A Novel Tool for Predicting an Abnormal Echocardiogram in Patients with Pulmonary Embolism: The PEACE Score.

The Journal of emergency medicine
BACKGROUND: Transthoracic echocardiography (TTE) is an essential tool for risk-stratifying patients with pulmonary embolism (PE), but its availability is limited, often requiring hospitalization. Minimal research exists evaluating clinical and labora...

Performance Analysis in Children of Traditional and Deep Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults.

AJR. American journal of roentgenology
Although primary lung cancer is rare in children, chest CT is commonly performed to assess for lung metastases in children with cancer. Lung nodule computer-aided detection (CAD) systems have been designed and studied primarily using adult training ...

Deep learning reconstruction for improving the visualization of acute brain infarct on computed tomography.

Neuroradiology
PURPOSE: This study aimed to investigate the impact of deep learning reconstruction (DLR) on acute infarct depiction compared with hybrid iterative reconstruction (Hybrid IR).

Application of CT and MRI images based on an artificial intelligence algorithm for predicting lymph node metastasis in breast cancer patients: a meta-analysis.

BMC cancer
BACKGROUND: This study aimed to comprehensively evaluate the accuracy and effect of computed tomography (CT) and magnetic resonance imaging (MRI) based on artificial intelligence (AI) algorithms for predicting lymph node metastasis in breast cancer p...

Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.

Scientific reports
Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application ...

Re-UNet: a novel multi-scale reverse U-shape network architecture for low-dose CT image reconstruction.

Medical & biological engineering & computing
In recent years, the growing awareness of public health has brought attention to low-dose computed tomography (LDCT) scans. However, the CT image generated in this way contains a lot of noise or artifacts, which make increasing researchers to investi...

The Role of Artificial Intelligence in Coronary Calcium Scoring in Standard Cardiac Computed Tomography and Chest Computed Tomography With Different Reconstruction Kernels.

Journal of thoracic imaging
PURPOSE: To assess the correlation of coronary calcium score (CS) obtained by artificial intelligence (AI) with those obtained by electrocardiography gated standard cardiac computed tomography (CCT) and nongated chest computed tomography (ChCT) with ...