AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Intelligent diagnosis model for chest X-ray images diseases based on convolutional neural network.
BMC medical imaging
Jul 2, 2025
To address misdiagnosis caused by feature coupling in multi-label medical image classification, this study introduces a chest X-ray pathology reasoning method. It combines hierarchical attention convolutional networks with a multi-label decoupling lo...
A deep learning-based computed tomography reading system for the diagnosis of lung cancer associated with cystic airspaces.
Scientific reports
Jul 2, 2025
To propose a deep learning model and explore its performance in the auxiliary diagnosis of lung cancer associated with cystic airspaces (LCCA) in computed tomography (CT) images. This study is a retrospective analysis that incorporated a total of 342...
Artificial Intelligence Iterative Reconstruction for Dose Reduction in Pediatric Chest CT: A Clinical Assessment via Below 3 Years Patients With Congenital Heart Disease.
Journal of thoracic imaging
Jul 1, 2025
PURPOSE: To assess the performance of a newly introduced deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in reducing the dose of pediatric chest CT by using the image data of below 3-y...
Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray.
PloS one
Jun 25, 2025
Thoracic diseases, including pneumonia, tuberculosis, lung cancer, and others, pose significant health risks and require timely and accurate diagnosis to ensure proper treatment. Thus, in this research, a model for thorax disease classification using...
Ultra-High-Resolution Photon-Counting-Detector CT with a Dedicated Denoising Convolutional Neural Network for Enhanced Temporal Bone Imaging.
AJNR. American journal of neuroradiology
Jun 3, 2025
BACKGROUND AND PURPOSE: Ultra-high-resolution (UHR) photon-counting-detector (PCD) CT improves image resolution but increases noise, necessitating the use of smoother reconstruction kernels that reduce resolution below the 0.125-mm maximum spatial re...
Multi-spatial-attention U-Net: a novel framework for automated gallbladder segmentation on CT images.
BMC medical imaging
May 30, 2025
OBJECTIVE: This study aimed to construct a novel model, Multi-Spatial Attention U-Net (MSAU-Net) by incorporating our proposed Multi-Spatial Attention (MSA) block into the U-Net for the automated segmentation of the gallbladder on CT images.
Deep Learning-enhanced Opportunistic Osteoporosis Screening in Ultralow-Voltage (80 kV) Chest CT: A Preliminary Study.
Academic radiology
May 2, 2025
RATIONALE AND OBJECTIVES: To explore the feasibility of deep learning (DL)-enhanced, fully automated bone mineral density (BMD) measurement using the ultralow-voltage 80 kV chest CT scans performed for lung cancer screening.
A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.
BMC medical imaging
May 1, 2025
BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for adrenal CT measurements in clinical practice. This study aims to develop a deep learning (DL) model for automated adrenal gland segmentation on non-con...
Impact of Photon-counting Detector Computed Tomography on a Quantitative Interstitial Lung Disease Machine Learning Model.
Journal of thoracic imaging
May 1, 2025
PURPOSE: Compare the impact of photon-counting detector computed tomography (PCD-CT) to conventional CT on an interstitial lung disease (ILD) quantitative machine learning (QML) model.
Detection of Pulmonary Nodules on Ultra-low Dose Chest Computed Tomography With Deep-learning Image Reconstruction Algorithm.
Journal of thoracic imaging
May 1, 2025
PURPOSE: To evaluate the accuracy of ultra-low dose (ULD) chest computed tomography (CT), with a radiation exposure equivalent to a 2-view chest x-ray, for pulmonary nodule detection using deep learning image reconstruction (DLIR).
Sensitivity and Specificity
Cross-Sectional Studies
Male
Middle Aged
Humans
Lung
Deep Learning
Female
Lung Neoplasms
Algorithms
Aged
Radiation Dosage
Prospective Studies
Aged, 80 and over
Multiple Pulmonary Nodules
Radiography, Thoracic
Tomography, X-Ray Computed
Adult
Solitary Pulmonary Nodule
Radiographic Image Interpretation, Computer-Assisted
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