AIMC Topic: Radiographic Image Enhancement

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Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.

Journal of applied clinical medical physics Nov 14, 2024
OBJECTIVE: We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy.
Humans Algorithms Prospective Studies Tomography, X-Ray Computed Female Signal-To-Noise Ratio Pelvic Neoplasms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiotherapy, Image-Guided Radiographic Image Enhancement Phantoms, Imaging Abdominal Neoplasms Feasibility Studies Organs at Risk Radiotherapy Planning, Computer-Assisted Radiation Dosage Male Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted
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Impact of deep Learning-enhanced contrast on diagnostic accuracy in stroke CT angiography.

European journal of radiology Oct 28, 2024
PURPOSE: To examine the impact of deep learning-augmented contrast enhancement on image quality and diagnostic accuracy of poorly contrasted CT angiography in patients with suspected stroke.
Deep Learning Contrast Media Radiographic Image Interpretation, Computer-Assisted Stroke Aged Sensitivity and Specificity Male Middle Aged Signal-To-Noise Ratio Computed Tomography Angiography Cerebral Angiography Radiographic Image Enhancement Humans Retrospective Studies Female Reproducibility of Results
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Application of a Deep Learning-Based Contrast-Boosting Algorithm to Low-Dose Computed Tomography Pulmonary Angiography With Reduced Iodine Load.

Journal of computer assisted tomography Oct 10, 2024
OBJECTIVE: The aim of this study was to assess the effectiveness of a deep learning-based image contrast-boosting algorithm by enhancing the image quality of low-dose computed tomography pulmonary angiography at reduced iodine load.
Aged, 80 and over Adult Male Middle Aged Algorithms Retrospective Studies Female Aged Pulmonary Embolism Humans Radiation Dosage Deep Learning Computed Tomography Angiography Iodine Radiographic Image Enhancement Contrast Media Pulmonary Artery Radiographic Image Interpretation, Computer-Assisted
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A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.

BMC medical imaging Jul 1, 2024
PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose redu...
Phlebography Femoral Vein Varicose Veins Popliteal Vein Radiation Dosage Vena Cava, Inferior Computed Tomography Angiography Retrospective Studies Radiographic Image Enhancement Venous Thrombosis Tomography, X-Ray Computed Contrast Media Female Lower Extremity Aged Radiographic Image Interpretation, Computer-Assisted Humans Male Aged, 80 and over Algorithms Middle Aged Adult Deep Learning
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A deep learning approach for virtual contrast enhancement in Contrast Enhanced Spectral Mammography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society May 23, 2024
Contrast Enhanced Spectral Mammography (CESM) is a dual-energy mammographic imaging technique that first requires intravenously administering an iodinated contrast medium. Then, it collects both a low-energy image, comparable to standard mammography,...
Mammography Radiographic Image Interpretation, Computer-Assisted Radiographic Image Enhancement Female Breast Neoplasms Deep Learning Contrast Media Humans
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A deep-learning-based scatter correction with water equivalent path length map for digital radiography.

Radiological physics and technology May 2, 2024
We proposed a new deep learning (DL) model for accurate scatter correction in digital radiography. The proposed network featured a pixel-wise water equivalent path length (WEPL) map of subjects with diverse sizes and 3D inner structures. The proposed...
Humans Deep Learning Water Imaging, Three-Dimensional Algorithms Phantoms, Imaging Tomography, X-Ray Computed Radiographic Image Enhancement Image Processing, Computer-Assisted Signal-To-Noise Ratio Monte Carlo Method Scattering, Radiation
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A Deep-Learning Model for Predicting the Efficacy of Non-vascularized Fibular Grafting Using Digital Radiography.

Academic radiology Nov 5, 2023
RATIONALE AND OBJECTIVES: To develop a fully automated deep-learning (DL) model using digital radiography (DR) with relatively high accuracy for predicting the efficacy of non-vascularized fibular grafting (NVFG) and identifying suitable patients for...
Treatment Outcome Radiographic Image Enhancement Femur Head Necrosis Humans Retrospective Studies Deep Learning
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Deep learning, radiomics and radiogenomics applications in the digital breast tomosynthesis: a systematic review.

BMC bioinformatics Oct 26, 2023
BACKGROUND: Recent advancements in computing power and state-of-the-art algorithms have helped in more accessible and accurate diagnosis of numerous diseases. In addition, the development of de novo areas in imaging science, such as radiomics and rad...
Humans Breast Female Radiographic Image Enhancement Breast Neoplasms Deep Learning Mammography
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Incidental radiological findings during clinical tuberculosis screening in Lesotho and South Africa: a case series.

Journal of medical case reports Aug 25, 2023
BACKGROUND: Chest X-ray offers high sensitivity and acceptable specificity as a tuberculosis screening tool, but in areas with a high burden of tuberculosis, there is often a lack of radiological expertise to interpret chest X-ray. Computer-aided det...
South Africa Radiographic Image Enhancement Humans Lesotho Artificial Intelligence Female Adult Young Adult Male Middle Aged Radiography
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A deep learning approach to estimate x-ray scatter in digital breast tomosynthesis: From phantom models to clinical applications.

Medical physics Jul 2, 2023
BACKGROUND: Digital breast tomosynthesis (DBT) has gained popularity as breast imaging modality due to its pseudo-3D reconstruction and improved accuracy compared to digital mammography. However, DBT faces challenges in image quality and quantitative...
Monte Carlo Method Deep Learning Humans Phantoms, Imaging Mammography Neural Networks, Computer X-Rays Breast Female Radiographic Image Enhancement Datasets as Topic Breast Neoplasms
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