AIMC Topic: Tomography, X-Ray Computed
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Determination of the oral carcinoma and sarcoma in contrast enhanced CT images using deep convolutional neural networks.
Scientific reports
Jul 1, 2025
Oral cancer is a hazardous disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop the deep convolutional neural networks (CNN)-based multiclass classification and object detection models for distingui...
Evaluation of MRI-based synthetic CT for lumbar degenerative disease: a comparison with CT.
Scientific reports
Jul 1, 2025
Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans, but this approach introduces additional ionizing radiation and examination costs. To compare the effectiveness of MRI-based synthetic CT (sCT) in dis...
AI-based CT assessment of 3117 vertebrae reveals significant sex-specific vertebral height differences.
Scientific reports
Jul 1, 2025
Predicting vertebral height is complex due to individual factors. AI-based medical imaging analysis offers new opportunities for vertebral assessment. Thereby, these novel methods may contribute to sex-adapted nomograms and vertebral height predictio...
Synergizing advanced algorithm of explainable artificial intelligence with hybrid model for enhanced brain tumor detection in healthcare.
Scientific reports
Jul 1, 2025
Brain tumor causes life-threatening consequences due to which its timely detection and accurate classification are critical for determining appropriate treatment plans while focusing on the improved patient outcomes. However, conventional approaches ...
Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer.
Scientific reports
Jul 1, 2025
Reconstructive flap surgery aims to restore the substance and function losses associated with tumor resection. Automatic flap segmentation could allow quantification of flap volume and correlations with functional outcomes after surgery or post-opera...
Automated classification of chondroid tumor using 3D U-Net and radiomics with deep features.
Scientific reports
Jul 1, 2025
Classifying chondroid tumors is an essential step for effective treatment planning. Recently, with the advances in computer-aided diagnosis and the increasing availability of medical imaging data, automated tumor classification using deep learning sh...
Multi-modal and Multi-view Cervical Spondylosis Imaging Dataset.
Scientific data
Jul 1, 2025
Multi-modal and multi-view imaging is essential for diagnosis and assessment of cervical spondylosis. Deep learning has increasingly been developed to assist in diagnosis and assessment, which can help improve clinical management and provide new idea...
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...
Radiomic 'Stress Test': exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort.
BMJ open respiratory research
Jun 27, 2025
BACKGROUND: Indeterminate pulmonary nodules (IPNs) are commonly biopsied to ascertain a diagnosis of lung cancer, but many are ultimately benign. The Lung Cancer Prediction (LCP) score is a commercially available deep learning radiomic model with str...
Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis.
RMD open
Jun 25, 2025
INTRODUCTION: Systemic sclerosis (SSc) is a complex inflammatory vasculopathy with diverse symptoms and variable disease progression. Despite its known impact on body composition (BC), clinical decision-making has yet to incorporate these biomarkers....
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