AIMC Topic: Radiographic Image Enhancement

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Deep Learning for Contrast Enhanced Mammography - A Systematic Review.

Academic radiology Dec 5, 2024
BACKGROUND/AIM: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that enables both anatomical and functional breast imaging, with improved diagnostic performance compared to standard 2D mammography. The aim of this study is...
Humans Radiographic Image Interpretation, Computer-Assisted Female Contrast Media Radiographic Image Enhancement Mammography Breast Neoplasms Deep Learning
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Contrast-enhanced thin-slice abdominal CT with super-resolution deep learning reconstruction technique: evaluation of image quality and visibility of anatomical structures.

Japanese journal of radiology Nov 14, 2024
PURPOSE: To compare image quality and visibility of anatomical structures on contrast-enhanced thin-slice abdominal CT images reconstructed using super-resolution deep learning reconstruction (SR-DLR), deep learning-based reconstruction (DLR), and hy...
Retrospective Studies Tomography, X-Ray Computed Female Aged Aged, 80 and over Humans Contrast Media Radiographic Image Interpretation, Computer-Assisted Radiographic Image Enhancement Radiography, Abdominal Adult Male Middle Aged Deep Learning
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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.
Pelvic Neoplasms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Phantoms, Imaging Organs at Risk Radiotherapy Planning, Computer-Assisted Radiation Dosage Signal-To-Noise Ratio Abdominal Neoplasms Radiotherapy, Image-Guided Radiographic Image Enhancement Prospective Studies Tomography, X-Ray Computed Female Male Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Humans Algorithms
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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.
Cerebral Angiography Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Stroke Signal-To-Noise Ratio Computed Tomography Angiography Retrospective Studies Female Reproducibility of Results Aged Middle Aged Deep Learning Contrast Media Humans Sensitivity and Specificity Male
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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 Radiation Dosage Computed Tomography Angiography Radiographic Image Enhancement Humans Pulmonary Artery Deep Learning Iodine Contrast Media 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...
Male Middle Aged Deep Learning Venous Thrombosis Contrast Media Lower Extremity Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Female Femoral Vein Humans Aged Vena Cava, Inferior Varicose Veins Algorithms Aged, 80 and over Computed Tomography Angiography Popliteal Vein Retrospective Studies Adult Radiographic Image Enhancement Tomography, X-Ray Computed Phlebography
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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,...
Radiographic Image Enhancement Humans Deep Learning Female Contrast Media Breast Neoplasms Mammography Radiographic Image Interpretation, Computer-Assisted
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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 Algorithms Tomography, X-Ray Computed Signal-To-Noise Ratio Deep Learning Scattering, Radiation Water Monte Carlo Method Phantoms, Imaging Imaging, Three-Dimensional Radiographic Image Enhancement Image Processing, Computer-Assisted
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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...
Retrospective Studies Deep Learning Treatment Outcome Radiographic Image Enhancement Humans Femur Head Necrosis
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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...
Mammography Humans Breast Female Radiographic Image Enhancement Breast Neoplasms Deep Learning
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