AIMC Topic: Radiographic Image Enhancement
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Deep Learning-Based Reconstruction Algorithm With Lung Enhancement Filter for Chest CT: Effect on Image Quality and Ground Glass Nodule Sharpness.
Korean journal of radiology
Sep 1, 2024
OBJECTIVE: To assess the effect of a new lung enhancement filter combined with deep learning image reconstruction (DLIR) algorithm on image quality and ground-glass nodule (GGN) sharpness compared to hybrid iterative reconstruction or DLIR alone.
AI Systems for Mammography with Digital Breast Tomosynthesis: Expectations and Challenges.
Radiology. Imaging cancer
Jul 1, 2024
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 ...
Invited Commentary: The Power and Promise of Artificial Intelligence for Digital Breast Tomosynthesis.
Radiographics : a review publication of the Radiological Society of North America, Inc
Jan 1, 2023
VIRTUAL CLINICAL TRIALS IN MEDICAL IMAGING SYSTEM EVALUATION AND OPTIMISATION.
Radiation protection dosimetry
Oct 12, 2021
Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs...
Differentiation of Intrahepatic Cholangiocarcinoma and Hepatic Lymphoma Based on Radiomics and Machine Learning in Contrast-Enhanced Computer Tomography.
Technology in cancer research & treatment
Jan 1, 2021
This study aimed to explore the ability of texture parameters combining with machine learning methods in distinguishing intrahepatic cholangiocarcinoma (ICCA) and hepatic lymphoma (HL). A total of 28 patients with HL and 101 patients with ICCA were...
Cholangiocarcinoma
Radiographic Image Enhancement
Neoplasm Grading
Tumor Burden
Bile Duct Neoplasms
Male
Middle Aged
ROC Curve
Contrast Media
Diagnosis, Differential
Humans
Image Processing, Computer-Assisted
Lymphoma
Female
Reproducibility of Results
Machine Learning
Aged
Algorithms
Tomography, X-Ray Computed
Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation.
The Lancet. Digital health
Jun 1, 2020
BACKGROUND: The diagnostic performance of CT for pancreatic cancer is interpreter-dependent, and approximately 40% of tumours smaller than 2 cm evade detection. Convolutional neural networks (CNNs) have shown promise in image analysis, but the networ...
Humans
Female
Reproducibility of Results
Retrospective Studies
Tomography, X-Ray Computed
Diagnosis, Differential
Pancreatic Neoplasms
Middle Aged
Radiographic Image Enhancement
Radiographic Image Interpretation, Computer-Assisted
Deep Learning
Aged
Pancreas
Contrast Media
Sensitivity and Specificity
Racial Groups
Taiwan
Male
Machine Learning and Deep Neural Networks: Applications in Patient and Scan Preparation, Contrast Medium, and Radiation Dose Optimization.
Journal of thoracic imaging
May 1, 2020
Artificial intelligence (AI) algorithms are dependent on a high amount of robust data and the application of appropriate computational power and software. AI offers the potential for major changes in cardiothoracic imaging. Beyond image processing, m...
Classification of Benign and Malignant Breast Masses on Mammograms for Large Datasets using Core Vector Machines.
Current medical imaging
Jan 1, 2020
BACKGROUND: Breast cancer is one of the most leading causes of cancer deaths among women. Early detection of cancer increases the survival rate of the affected women. Machine learning approaches that are used for classification of breast cancer usual...
Classification of Aortic Dissection and Rupture on Post-contrast CT Images Using a Convolutional Neural Network.
Journal of digital imaging
Dec 1, 2019
Aortic dissections and ruptures are life-threatening injuries that must be immediately treated. Our national radiology practice receives dozens of these cases each month, but no automated process is currently available to check for critical pathologi...
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