AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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A Preoperative CT-based Multiparameter Deep Learning and Radiomic Model with Extracellular Volume Parameter Images Can Predict the Tumor Budding Grade in Rectal Cancer Patients.

Academic radiology Mar 6, 2025
RATIONALE AND OBJECTIVES: To investigate a computed tomography (CT)-based multiparameter deep learning-radiomic model (DLRM) for predicting the preoperative tumor budding (TB) grade in patients with rectal cancer.
Female Aged Adult Radiomics Humans Retrospective Studies Tomography, X-Ray Computed Neoplasm Grading Radiographic Image Interpretation, Computer-Assisted Rectal Neoplasms Preoperative Care Male Middle Aged Deep Learning
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Learning Consistent Semantic Representation for Chest X-ray via Anatomical Localization in Self-Supervised Pre-Training.

IEEE journal of biomedical and health informatics Mar 6, 2025
Despite the similar global structures in Chest X-ray (CXR) images, the same anatomy exhibits varying appearances across images, including differences in local textures, shapes, colors, etc. Learning consistent representations for anatomical semantics...
Radiographic Image Interpretation, Computer-Assisted Supervised Machine Learning Semantics Radiography, Thoracic Thorax Humans Algorithms
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OMS-CNN: Optimized Multi-Scale CNN for Lung Nodule Detection Based on Faster R-CNN.

IEEE journal of biomedical and health informatics Mar 6, 2025
The global increase in lung cancer cases, often marked by pulmonary nodules, underscores the critical importance of timely detection to mitigate cancer progression and reduce morbidity and mortality. The Faster R-CNN approach is a two-stage, high-pre...
Humans Neural Networks, Computer Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Solitary Pulmonary Nodule Algorithms Tomography, X-Ray Computed Lung
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Automated classification of chest X-rays: a deep learning approach with attention mechanisms.

BMC medical imaging Mar 4, 2025
BACKGROUND: Pulmonary diseases such as COVID-19 and pneumonia, are life-threatening conditions, that require prompt and accurate diagnosis for effective treatment. Chest X-ray (CXR) has become the most common alternative method for detecting pulmonar...
COVID-19 SARS-CoV-2 Lung Radiography, Thoracic Pneumonia, Viral Deep Learning Radiographic Image Interpretation, Computer-Assisted Humans
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Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.

AJNR. American journal of neuroradiology Mar 4, 2025
BACKGROUND AND PURPOSE: ASPECTS is a long-standing and well-documented selection criterion for acute ischemic stroke treatment; however, the interpretation of ASPECTS is a challenging and time-consuming task for physicians with notable interobserver ...
Deep Learning Ischemic Stroke Radiographic Image Interpretation, Computer-Assisted Observer Variation Algorithms Retrospective Studies Reproducibility of Results Computed Tomography Angiography Humans
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Metastatic Lung Lesion Changes in Follow-up Chest CT: The Advantage of Deep Learning Simultaneous Analysis of Prior and Current Scans With SimU-Net.

Journal of thoracic imaging Mar 1, 2025
PURPOSE: Radiological follow-up of oncology patients requires the detection of metastatic lung lesions and the quantitative analysis of their changes in longitudinal imaging studies. Our aim was to evaluate SimU-Net, a novel deep learning method for ...
Lung Deep Learning Lung Neoplasms Radiography, Thoracic Follow-Up Studies Radiographic Image Interpretation, Computer-Assisted Aged Male Humans Middle Aged Tomography, X-Ray Computed Female
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Artificial intelligence quantification and experienced reader computed tomography analysis for differentiating normal from minimally and mildly diseased coronary arteries: an early real-world compatibility study.

The international journal of cardiovascular imaging Feb 28, 2025
Differentiating normal from minimally and mildly diseased coronary arteries on coronary computed tomographic angiography (CCTA) is crucial, impacting treatment decisions due to the extremely low coronary artery event risk associated with the former. ...
Retrospective Studies Female Reproducibility of Results Aged Humans Artificial Intelligence Predictive Value of Tests Coronary Artery Disease Coronary Angiography Asymptomatic Diseases Observer Variation Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Coronary Vessels Male Plaque, Atherosclerotic Middle Aged Vascular Calcification Severity of Illness Index
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Multi-axis transformer based U-Net with class balanced ensemble model for lung disease classification using X-ray images.

Journal of X-ray science and technology Feb 26, 2025
Chest X-rays are an essential diagnostic tool for identifying chest disorders because of its high sensitivity in detecting pathological anomalies in the lungs. Classification models based on conventional Convolutional Neural Networks (CNNs) are adve...
Radiographic Image Interpretation, Computer-Assisted Humans Lung Lung Diseases Neural Networks, Computer Radiography, Thoracic Algorithms Deep Learning Image Processing, Computer-Assisted
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ADMM-TransNet: ADMM-Based Sparse-View CT Reconstruction Method Combining Convolution and Transformer Network.

Tomography (Ann Arbor, Mich.) Feb 26, 2025
BACKGROUND: X-ray computed tomography (CT) imaging technology provides high-precision anatomical visualization of patients and has become a standard modality in clinical diagnostics. A widely adopted strategy to mitigate radiation exposure is sparse-...
Deep Learning Algorithms Image Processing, Computer-Assisted Tomography, X-Ray Computed Humans Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer
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Using deep learning to differentiate among histology renal tumor types in computed tomography scans.

BMC medical imaging Feb 26, 2025
BACKGROUND: This study employed a convolutional neural network (CNN) to analyze computed tomography (CT) scans with the aim of differentiating among renal tumors according to histologic sub-type.
Adenoma, Oxyphilic Kidney Neoplasms Carcinoma, Renal Cell Humans Angiomyolipoma Neural Networks, Computer Tomography, X-Ray Computed Female Middle Aged Aged Diagnosis, Differential Adult Deep Learning Radiographic Image Interpretation, Computer-Assisted Male
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