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Effective SNOMED-CT Concept Classification from Natural Language using Knowledge Distillation
Recently, as natural language processing (NLP) methods have been developed a lot, research on predicting rule languages such as medical terminology...
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Analysis of CT Images Using Quantum Edge Extraction Algorithm for the Assessment of Different Stages of COVID-19 Patient
The infected lung of COVID-19 patients has four stages–early, progressive, peak, and absorption. Clinical analysis is required for the treatment of...
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COVID-19 Classification of CT Lung Images Using Intelligent Wolf Optimization Based Deep Convolutional Neural Network
Chest computed tomography (CT) imaging is highly reliable and practical in diagnosing and analyzing COVID-19, mainly in the infectious region rather...
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X-Ray Multispectral CT Imaging by Projection Sequences Blind Separation Based on Basis-Effect or Basis-Material Decomposition
Multispectral CT is a promising method in material characterization, nondestructive evaluation, and other applications. For multispectral CT, the...
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Lung CT Image Segmentation via Dilated U-Net Model and Multi-scale Gray Correlation-Based Approach
Lung segmentation is a prerequisite for lung cancer diagnosis with computer-aided diagnosis systems. However, correct lung segmentation is a...
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Prediction and Classification of Aerosol Deposition in Lung Using CT Scan Images
Interstitial lung disease (ILD) is a set of chronic lung disorders that are essential for establishing treatment since the decisions are based on...
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Spatial map** of tumor heterogeneity in whole-body PET–CT: a feasibility study
BackgroundTumor heterogeneity is recognized as a predictor of treatment response and patient outcome. Quantification of tumor heterogeneity across...
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Application of the deep transfer learning framework for hydatid cyst classification using CT images
Hydatid cyst, which causes important public health problems, is a disease frequently reported by radiologists. Classification of hydatid cyst types...
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EGFR Mutation Prediction Using F18-FDG PET-CT Based Radiomics Features in Non-small Cell Lung Cancer
Lung cancer is the leading cause of cancer death in the world. Accurate determination of the EGFR (epidermal growth factor receptor) mutation status...
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Computational Approach for Verification of Aortic Wall Tear Size on CT Contrast Distribution in Patients with Type B Aortic Dissection—The Preliminary Study
The purpose of this research was to prepare a preliminary mathematical approach for the identification and analysis of the gap distribution using...
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Automated Lesion Image Segmentation Based on Novel Histogram-Based K-Means Clustering Using COVID-19 Chest CT Images
COVID-19 has wreaked havoc in the world, causing epidemic scenarios in the majority of countries. As a result, medical practitioners urgently seek an...
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Low-Dose CT Image Denoising with a Residual Multi-scale Feature Fusion Convolutional Neural Network and Enhanced Perceptual Loss
Computed tomography (CT) stands as a pivotal medical imaging technique, delivering timely and reliable clinical evaluations. Yet, its dependence on...
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SCTV-UNet: a COVID-19 CT segmentation network based on attention mechanism
The global outbreak of COVID-19 has become an important research topic in healthcare since 2019. RT-PCR is the main method for detecting COVID-19,...
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The Application Value of Virtual Reality Navigation Combined with Rapid On-Site Evaluation in CT-Guided Lung Biopsy
The purpose is to evaluate the value of Virtual Reality (VR) navigation system-assisted CT-guided percutaneous aspiration biopsy combined with Rapid...
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Deep learning-driven multi-view multi-task image quality assessment method for chest CT image
BackgroundChest computed tomography (CT) image quality impacts radiologists’ diagnoses. Pre-diagnostic image quality assessment is essential but...
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Visualization of Seepage Behavior in a Model Ground Around Sheet Pile Using μ-Focused X-Ray CT System
River levees are used for not only flood control, but also for flood inundation. In recent years, river floods caused by short duration torrential...
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CT and MRI multi-modal medical image fusion using weight-optimized anisotropic diffusion filtering
The purpose of multi-modal medical image fusion is to improve the accuracy of clinical diagnosis; the fused image is produced by retaining the...
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Lung cancer CT image classification using hybrid-SVM transfer learning approach
Lung cancer is a leading deadly form of the illness that is the cause of one million deaths around the world every year. Identification of lung...
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Unsupervised Domain Adaptation Approach for Liver Tumor Detection in Multi-phase CT Images
For computer-aided diagnosis, automatic and accurate liver tumor detection in multi-phase CT images is essential. Nowadays, deep learning has been...
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ODNN-LDA: Automated Lung Cancer Detection on CT Images Using an Optimal Deep Linear Discriminate Learning Model
Lung cancer is classified as one of the most common forms of cancer that cannot be ignored and can lead to death if treated late. According to the...