AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Bone-Cancer Assessment and Destruction Pattern Analysis in Long-Bone X-ray Image.

Journal of digital imaging Apr 1, 2019
Bone cancer originates from bone and rapidly spreads to the rest of the body affecting the patient. A quick and preliminary diagnosis of bone cancer begins with the analysis of bone X-ray or MRI image. Compared to MRI, an X-ray image provides a low-c...
Radiographic Image Interpretation, Computer-Assisted X-Rays Bone Neoplasms Humans Neoplasm Staging Support Vector Machine Neoplasm Grading Magnetic Resonance Imaging
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Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

Tomography (Ann Arbor, Mich.) Mar 1, 2019
We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre-...
Deep Learning ROC Curve Decision Support Systems, Clinical Treatment Outcome Tomography, X-Ray Computed Sensitivity and Specificity Antineoplastic Agents Radiographic Image Interpretation, Computer-Assisted Cystectomy Urography Transfer, Psychology Neoadjuvant Therapy Urinary Bladder Neoplasms Drug Monitoring Humans
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Limits on transfer learning from photographic image data to X-ray threat detection.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: X-ray imaging is a crucial and ubiquitous tool for detecting threats to transport security, but interpretation of the images presents a logistical bottleneck. Recent advances in Deep Learning image classification offer hope of improving t...
Aviation Deep Learning Radiographic Image Interpretation, Computer-Assisted Security Measures Photography
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Impact of Knowledge-Based Iterative Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic Myocardial Computed Tomography Perfusion Using Low-Tube-Voltage Scan: A Feasibility Study.

Journal of computer assisted tomography Jan 1, 2019
OBJECTIVE: Knowledge-based iterative model reconstruction (IMR) yields diagnostically acceptable image quality in low-dose static computed tomography (CT). We aimed to evaluate the feasibility of IMR in dynamic myocardial computed tomography perfusio...
Contrast Media Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Exercise Test Humans Male Middle Aged Female Hemodynamics Aged Multidetector Computed Tomography Algorithms Coronary Artery Disease Cardiac-Gated Imaging Techniques Retrospective Studies Computed Tomography Angiography Feasibility Studies Iopamidol Knowledge Bases
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New one-step model of breast tumor locating based on deep learning.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Breast cancer has the highest cancer prevalence rate among the women worldwide. Early detection of breast cancer is crucial for successful treatment and reducing cancer mortality rate. However, tumor detection of breast ultrasound (US) im...
Neural Networks, Computer Algorithms Female Breast Neoplasms Humans Deep Learning Radiographic Image Interpretation, Computer-Assisted Breast Image Processing, Computer-Assisted Ultrasonography, Mammary Mammography
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Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Deep learning has made spectacular achievements in analysing natural images, but it faces challenges for medical applications partly due to inadequate images.
Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Lung Humans Deep Learning Databases, Factual ROC Curve Tomography, X-Ray Computed Reproducibility of Results
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Breast mass detection and diagnosis using fused features with density.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: The morbidity of breast cancer has been increased in these years and ranked the first of all female diseases. Computer-aided diagnosis techniques for mammograms can help radiologists find early breast lesions. In mammograms, the degree of...
Female Aged Humans Databases, Factual Breast ROC Curve Adult Unsupervised Machine Learning Breast Neoplasms Mammography Middle Aged Radiographic Image Interpretation, Computer-Assisted
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Expert knowledge-infused deep learning for automatic lung nodule detection.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Computer aided detection (CADe) of pulmonary nodules from computed tomography (CT) is crucial for early diagnosis of lung cancer. Self-learned features obtained by training datasets via deep learning have facilitated CADe of the nodules. ...
Knowledge Bases Humans Multiple Pulmonary Nodules Neural Networks, Computer Solitary Pulmonary Nodule Deep Learning Radiographic Image Interpretation, Computer-Assisted Lung Neoplasms Tomography, X-Ray Computed Sensitivity and Specificity
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Evaluation of an AI-Based Detection Software for Acute Findings in Abdominal Computed Tomography Scans: Toward an Automated Work List Prioritization of Routine CT Examinations.

Investigative radiology Jan 1, 2019
OBJECTIVE: The aim of this study was to test the diagnostic performance of a deep learning-based triage system for the detection of acute findings in abdominal computed tomography (CT) examinations.
Algorithms Tomography, X-Ray Computed Sensitivity and Specificity Radiography, Abdominal Radiographic Image Interpretation, Computer-Assisted Radiology Information Systems Humans Artificial Intelligence
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3D deep learning for detecting pulmonary nodules in CT scans.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2018
OBJECTIVE: To demonstrate and test the validity of a novel deep-learning-based system for the automated detection of pulmonary nodules.
ROC Curve Lung Humans Radiographic Image Interpretation, Computer-Assisted Multiple Pulmonary Nodules Diagnosis, Computer-Assisted Tomography, X-Ray Computed Solitary Pulmonary Nodule Sensitivity and Specificity Deep Learning
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