AIMC Topic: Tomography, X-Ray Computed
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Accuracy of artificial intelligence-based segmentation in maxillofacial structures: a systematic review.
BMC oral health
Mar 7, 2025
OBJECTIVE: The aim of this review was to evaluate the accuracy of artificial intelligence (AI) in the segmentation of teeth, jawbone (maxilla, mandible with temporomandibular joint), and mandibular (inferior alveolar) canal in CBCT and CT scans.
DeepOptimalNet: optimized deep learning model for early diagnosis of pancreatic tumor classification in CT imaging.
Abdominal radiology (New York)
Mar 6, 2025
Computed Tomography (CT) imaging captures detailed cross-sectional images of the pancreas and surrounding structures and provides valuable information for medical professionals. The classification of pancreatic CT images presents significant challeng...
Interstitial-guided automatic clinical tumor volume segmentation network for cervical cancer brachytherapy.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 6, 2025
Automatic clinical tumor volume (CTV) delineation is pivotal to improving outcomes for interstitial brachytherapy cervical cancer. However, the prominent differences in gray values due to the interstitial needles bring great challenges on deep learni...
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.
AI integrations with lung cancer screening: Considerations in developing AI in a public health setting.
European journal of cancer (Oxford, England : 1990)
Mar 6, 2025
Lung cancer screening implementation has led to expanded imaging of the chest in older, tobacco-exposed populations. Growing numbers of screening cases are also found to have CT-detectable emphysema or elevated levels of coronary calcium, indicating ...
Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 6, 2025
BACKGROUND: Apart from rare cases such as lymphomas, germ cell tumors, neuroendocrine neoplasms, and thymic hyperplasia, thymic mass lesions (TMLs) are typically categorized into cysts, and thymomas. However, the classification results cannot be dete...
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences.
Nature communications
Mar 6, 2025
Pulmonary artery-vein segmentation is critical for disease diagnosis and surgical planning. Traditional methods rely on Computed Tomography Pulmonary Angiography (CTPA), which requires contrast agents with potential health risks. Non-contrast CT, a s...
LUCF-Net: Lightweight U-Shaped Cascade Fusion Network for Medical Image Segmentation.
IEEE journal of biomedical and health informatics
Mar 6, 2025
The performance of modern U-shaped neural networks for medical image segmentation has been significantly enhanced by incorporating Transformer layers. Although Transformer architectures are powerful at extracting global information, its ability to ca...
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...
CDAF-Net: A Contextual Contrast Detail Attention Feature Fusion Network for Low-Dose CT Denoising.
IEEE journal of biomedical and health informatics
Mar 6, 2025
Low-dose computed tomography (LDCT) is a specialized CT scan with a lower radiation dose than normal-dose CT. However, the reduced radiation dose can introduce noise and artifacts, affecting diagnostic accuracy. To enhance the LDCT image quality, we ...
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