AI Medical Compendium Topic:
Radiographic Image Interpretation, Computer-Assisted

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Utilizing Pseudo Color Image to Improve the Performance of Deep Transfer Learning-Based Computer-Aided Diagnosis Schemes in Breast Mass Classification.

Journal of imaging informatics in medicine Jun 1, 2025
The purpose of this study is to investigate the impact of using morphological information in classifying suspicious breast lesions. The widespread use of deep transfer learning can significantly improve the performance of the mammogram based CADx sch...
Diagnosis, Computer-Assisted Deep Learning Mammography Color Female Breast Neoplasms Middle Aged Radiographic Image Interpretation, Computer-Assisted Humans Retrospective Studies
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A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult.

Journal of imaging informatics in medicine Jun 1, 2025
This study aims to investigate whether global mammographic radiomic features (GMRFs) can distinguish hardest- from easiest-to-interpret normal cases for radiology trainees (RTs). Data from 137 RTs were analysed, with each interpreting seven education...
Female Adult Breast Neoplasms Radiomics Humans Machine Learning Clinical Competence Radiographic Image Interpretation, Computer-Assisted Mammography Radiology
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Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles.

Journal of imaging informatics in medicine Jun 1, 2025
Techniques are developed for generating uncertainty estimates for convolutional neural network (CNN)-based methods for registering the locations of lesions between the craniocaudal (CC) and mediolateral oblique (MLO) mammographic X-ray image views. M...
Female Humans Breast Neoplasms Neural Networks, Computer Deep Learning Algorithms Mammography Radiographic Image Interpretation, Computer-Assisted Uncertainty
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Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.

Journal of imaging informatics in medicine Jun 1, 2025
To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA) under different tube voltages between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASIR-V). Three ...
Aged Adult Male Middle Aged Algorithms Humans Radiographic Image Interpretation, Computer-Assisted Prospective Studies Deep Learning Coronary Vessels Female Image Processing, Computer-Assisted Computed Tomography Angiography Adipose Tissue Epicardial Adipose Tissue Coronary Angiography
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Deep learning reconstruction improves computer-aided pulmonary nodule detection and measurement accuracy for ultra-low-dose chest CT.

BMC medical imaging May 30, 2025
PURPOSE: To compare the image quality and pulmonary nodule detectability and measurement accuracy between deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) of chest ultra-low-dose CT (ULDCT).
Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Adult Male Middle Aged Deep Learning Tomography, X-Ray Computed Female Aged Humans Prospective Studies
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Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images.

BMC musculoskeletal disorders May 20, 2025
OBJECTIVE: The aim of this study was to develop a hybrid diagnostic framework integrating radiomic and deep features for accurate and reproducible detection and classification of wrist fractures using X-ray images.
Adult Deep Learning Humans Wrist Injuries Radiomics Fractures, Bone Wrist Fractures Male Female Radiography Middle Aged Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted
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A clinically applicable AI system for detection and diagnosis of bone metastases using CT scans.

Nature communications May 13, 2025
Manual interpretation of CT images for bone metastasis (BM) detection in primary cancer remains challenging. We present an automated Bone Lesion Detection System (BLDS) developed using CT scans from 2518 patients (9177 BMs; 12,824 non-BM lesions) acr...
Adult Sensitivity and Specificity Male Middle Aged Bone Neoplasms Radiologists Radiographic Image Interpretation, Computer-Assisted Artificial Intelligence Humans Tomography, X-Ray Computed Female Aged
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Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: The aim of the study was to evaluate the image quality of coronary computed tomography (CT) angiography (CCTA) in obese patients by using deep learning image reconstruction (DLIR) in comparison with adaptive statistical iterative reconstru...
Deep Learning Radiographic Image Interpretation, Computer-Assisted Aged Obesity Humans Coronary Vessels Adult Coronary Angiography Prospective Studies Radiation Dosage Male Female Middle Aged Computed Tomography Angiography
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In Vitro Study of the Precision and Accuracy of Measurement of the Vascular Inner Diameter on Computed Tomography Angiography Using Deep Learning Image Reconstruction: Comparison With Filtered Back Projection and Iterative Reconstruction.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: This study aimed to compare the performance of deep learning image reconstruction (DLIR) with that of standard filtered back projection (FBP) and adaptive statistical iterative reconstruction V (ASiR-V) for measurement of the vascular diam...
Phantoms, Imaging Algorithms Computed Tomography Angiography Deep Learning Models, Cardiovascular Radiographic Image Interpretation, Computer-Assisted
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Artificial Intelligence in Diagnostic Radiology: Where Do We Stand, Challenges, and Opportunities.

Journal of computer assisted tomography May 13, 2025
Artificial intelligence (AI) is the most revolutionizing development in the health care industry in the current decade, with diagnostic imaging having the greatest share in such development. Machine learning and deep learning (DL) are subclasses of A...
Workflow Quality Control Humans Algorithms Tomography, X-Ray Computed Neural Networks, Computer Neoplasms Artificial Intelligence Radiographic Image Interpretation, Computer-Assisted Machine Learning
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