AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning.

Computers in biology and medicine Apr 12, 2018
Digital breast tomosynthesis (DBT) was developed in the field of breast cancer screening as a new tomographic technique to minimize the limitations of conventional digital mammography breast screening methods. A computer-aided detection (CAD) framewo...
Humans Deep Learning Mammography Radiographic Image Interpretation, Computer-Assisted Breast Algorithms Female Breast Neoplasms
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Relative location prediction in CT scan images using convolutional neural networks.

Computer methods and programs in biomedicine Mar 28, 2018
BACKGROUND AND OBJECTIVE: Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and spee...
Machine Learning Algorithms Databases, Factual Tomography, X-Ray Computed Humans Neural Networks, Computer Regression Analysis Radiographic Image Interpretation, Computer-Assisted Female Male Neck
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Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Medical image analysis Mar 27, 2018
Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate qu...
Artifacts Pattern Recognition, Automated Neural Networks, Computer Computed Tomography Angiography Contrast Media Aortic Aneurysm, Abdominal Humans Radiographic Image Interpretation, Computer-Assisted Thrombosis
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Deep learning in mammography and breast histology, an overview and future trends.

Medical image analysis Mar 26, 2018
Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promisin...
Humans Neural Networks, Computer Diagnosis, Computer-Assisted Female Algorithms Radiographic Image Interpretation, Computer-Assisted Deep Learning Sensitivity and Specificity Forecasting Mammography Breast Neoplasms Phenotype
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Artificial Intelligence and Radiology: Collaboration Is Key.

Journal of the American College of Radiology : JACR Feb 2, 2018
Optimism Artificial Intelligence Algorithms Forecasting Radiographic Image Interpretation, Computer-Assisted Radiology Information Systems Decision Support Techniques Deep Learning Humans
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Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.

Physics in medicine and biology Jan 30, 2018
In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally ...
Aged Aged, 80 and over Young Adult Middle Aged Risk Assessment Adult Breast Neoplasms Machine Learning Algorithms Female Image Processing, Computer-Assisted Breast Humans Mammography Breast Density Radiographic Image Interpretation, Computer-Assisted
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Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.

Physics in medicine and biology Jan 9, 2018
Breast density is one of the most significant factors that is associated with cancer risk. In this study, our purpose was to develop a supervised deep learning approach for automated estimation of percentage density (PD) on digital mammograms (DMs). ...
Breast Breast Density Female Aged Models, Statistical Aged, 80 and over Mammography Middle Aged Radiographic Image Interpretation, Computer-Assisted Humans Adult Deep Learning Retrospective Studies Breast Neoplasms
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Lung Lesion Detection in CT Scan Images Using the Fuzzy Local Information Cluster Means (FLICM) Automatic Segmentation Algorithm and Back Propagation Network Classification.

Asian Pacific journal of cancer prevention : APJCP Dec 29, 2017
Lung cancer is a frequently lethal disease often causing death of human beings at an early age because of uncontrolled cell growth in the lung tissues. The diagnostic methods available are less than effective for detection of cancer. Therefore an aut...
Fuzzy Logic Radiographic Image Interpretation, Computer-Assisted Algorithms Pattern Recognition, Automated Diagnosis, Computer-Assisted Tomography, X-Ray Computed Humans Image Processing, Computer-Assisted Neural Networks, Computer Lung Neoplasms
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Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

Radiological physics and technology Dec 28, 2017
Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tr...
X-Rays Fiducial Markers Humans Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Machine Learning Fluoroscopy Algorithms Pattern Recognition, Automated Tomography, X-Ray Computed
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Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks.

Clinical radiology Dec 18, 2017
AIM: To identify the extent to which transfer learning from deep convolutional neural networks (CNNs), pre-trained on non-medical images, can be used for automated fracture detection on plain radiographs.
Fractures, Bone Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Machine Learning Humans Sensitivity and Specificity Neural Networks, Computer Deep Learning Artificial Intelligence
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