AI Medical Compendium Journal:
Journal of X-ray science and technology

Showing 31 to 40 of 116 articles

Revolutionizing tumor detection and classification in multimodality imaging based on deep learning approaches: Methods, applications and limitations.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: The emergence of deep learning (DL) techniques has revolutionized tumor detection and classification in medical imaging, with multimodal medical imaging (MMI) gaining recognition for its precision in diagnosis, treatment, and progression ...
Deep Learning Humans Multimodal Imaging Neural Networks, Computer Neoplasms
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X-ray image enhancement with multi-scale local edge preserving filter based on fuzzy entropy.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: Recently, X-rays have been widely used to detect complex structural workpieces. Due to the uneven thickness of the workpiece and the high dynamic range of the X-ray image itself, the detailed internal structure of the workpiece cannot be ...
Algorithms Humans Entropy Image Processing, Computer-Assisted Fuzzy Logic Radiographic Image Enhancement
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Predicting patient-specific organ doses from thoracic CT examinations using support vector regression algorithm.

Journal of X-ray science and technology Jan 1, 2024
PURPOSE: This study aims to propose and develop a fast, accurate, and robust prediction method of patient-specific organ doses from CT examinations using minimized computational resources.
Aged Adult Male Algorithms Tomography, X-Ray Computed Middle Aged Humans Radiation Dosage Female Radiography, Thoracic Lung Support Vector Machine Monte Carlo Method
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DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid r...
Deep Learning Coronavirus Infections Semantics Radiography, Thoracic Betacoronavirus Pneumonia, Viral Algorithms SARS-CoV-2 Lung Neural Networks, Computer Pandemics COVID-19 Humans
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A user-friendly deep learning application for accurate lung cancer diagnosis.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: Accurate diagnosis and subsequent delineated treatment planning require the experience of clinicians in the handling of their case numbers. However, applying deep learning in image processing is useful in creating tools that promise faste...
Lung Deep Learning Imaging, Three-Dimensional Aged Image Processing, Computer-Assisted Humans Male Lung Neoplasms Tomography, X-Ray Computed Middle Aged Female
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CT-based intratumoral and peritumoral deep transfer learning features prediction of lymph node metastasis in non-small cell lung cancer.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: The main metastatic route for lung cancer is lymph node metastasis, and studies have shown that non-small cell lung cancer (NSCLC) has a high risk of lymph node infiltration.
Deep Learning Lung Neoplasms Lymph Nodes Carcinoma, Non-Small-Cell Lung Lymphatic Metastasis Humans Retrospective Studies Adult Male Middle Aged Tomography, X-Ray Computed Female Aged
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A hybrid thyroid tumor type classification system using feature fusion, multilayer perceptron and bonobo optimization.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: Thyroid tumor is considered to be a very rare form of cancer. But recent researches and surveys highlight the fact that it is becoming prevalent these days because of various factors.
Sensitivity and Specificity Thyroid Gland Thyroid Neoplasms Neural Networks, Computer Artificial Intelligence Algorithms Ultrasonography Image Interpretation, Computer-Assisted Humans
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Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study.

Journal of X-ray science and technology Jan 1, 2024
OBJECTIVES: To evaluate the performance of deep learning image reconstruction (DLIR) algorithm in dual-energy spectral CT (DEsCT) as a function of radiation dose and image energy level, in comparison with filtered-back-projection (FBP) and adaptive s...
Algorithms Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Humans Radiography, Dual-Energy Scanned Projection Radiation Dosage Signal-To-Noise Ratio Phantoms, Imaging
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Machine learning framework for simulation of artifacts in paranasal sinuses diagnosis using CT images.

Journal of X-ray science and technology Jan 1, 2024
In the medical field, diagnostic tools that make use of deep neural networks have reached a level of performance never before seen. A proper diagnosis of a patient's condition is crucial in modern medicine since it determines whether or not the patie...
Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted Paranasal Sinuses Humans Artifacts Machine Learning Paranasal Sinus Diseases
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Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography.

Journal of X-ray science and technology Jan 1, 2024
PURPOSE: The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesions presenting as only calcification on routine mammogram.
Aged Mammography Middle Aged Adult Diagnosis, Differential Breast Neoplasms Contrast Media Radiographic Image Interpretation, Computer-Assisted Humans Calcinosis Breast Machine Learning Female
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