AIMC Topic:
Image Interpretation, Computer-Assisted

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Artificial Intelligence and Stroke Imaging: A West Coast Perspective.

Neuroimaging clinics of North America Sep 18, 2020
Artificial intelligence (AI) advancements have significant implications for medical imaging. Stroke is the leading cause of disability and the fifth leading cause of death in the United States. AI applications for stroke imaging are a topic of intens...
Stroke Image Interpretation, Computer-Assisted Neuroimaging United States Diagnostic Imaging Artificial Intelligence Humans Brain
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Overview of Machine Learning: Part 2: Deep Learning for Medical Image Analysis.

Neuroimaging clinics of North America Sep 18, 2020
Deep learning has contributed to solving complex problems in science and engineering. This article provides the fundamental background required to understand and develop deep learning models for medical imaging applications. The authors review the ma...
Humans Machine Learning Image Interpretation, Computer-Assisted Neuroimaging Deep Learning
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Artificial intelligence in paediatric radiology: Future opportunities.

The British journal of radiology Sep 17, 2020
Artificial intelligence (AI) has received widespread and growing interest in healthcare, as a method to save time, cost and improve efficiencies. The high-performance statistics and diagnostic accuracies reported by using AI algorithms (with respect ...
Image Interpretation, Computer-Assisted Radiology Pediatrics Humans Artificial Intelligence Child Clinical Decision-Making Diagnostic Imaging
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Diverse Applications of Artificial Intelligence in Neuroradiology.

Neuroimaging clinics of North America Sep 17, 2020
Recent advances in artificial intelligence (AI) and deep learning (DL) hold promise to augment neuroimaging diagnosis for patients with brain tumors and stroke. Here, the authors review the diverse landscape of emerging neuroimaging applications of A...
Brain Diseases Brain Neuroimaging Humans Diagnostic Imaging Artificial Intelligence Image Interpretation, Computer-Assisted
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An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage.

Neuroimaging clinics of North America Sep 17, 2020
Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. This article reviews the use of deep learning convolut...
Image Interpretation, Computer-Assisted Machine Learning Triage Humans Brain Neuroimaging Diagnostic Imaging Artificial Intelligence United States Hemorrhagic Stroke
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Knowledge Based Versus Data Based: A Historical Perspective on a Continuum of Methodologies for Medical Image Analysis.

Neuroimaging clinics of North America Sep 17, 2020
The advent of big data and deep learning algorithms has promoted a major shift toward data-driven methods in medical image analysis recently. However, the medical image analysis field has a long and rich history inclusive of both knowledge-driven and...
Machine Learning Image Interpretation, Computer-Assisted Humans Neuroimaging Artificial Intelligence
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A Neural Network for Image Anomaly Detection with Deep Pyramidal Representations and Dynamic Routing.

International journal of neural systems Sep 16, 2020
Image anomaly detection is an application-driven problem where the aim is to identify novel samples, which differ significantly from the normal ones. We here propose Pyramidal Image Anomaly DEtector (PIADE), a deep reconstruction-based pyramidal appr...
Image Processing, Computer-Assisted Supervised Machine Learning Image Interpretation, Computer-Assisted Humans Deep Learning
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Automatic detection of non-perfusion areas in diabetic macular edema from fundus fluorescein angiography for decision making using deep learning.

Scientific reports Sep 15, 2020
Vision loss caused by diabetic macular edema (DME) can be prevented by early detection and laser photocoagulation. As there is no comprehensive detection technique to recognize NPA, we proposed an automatic detection method of NPA on fundus fluoresce...
Humans Diabetic Retinopathy Prognosis Female Aged Neural Networks, Computer Algorithms Image Interpretation, Computer-Assisted Fluorescein Angiography Deep Learning Follow-Up Studies Fundus Oculi Macular Edema Decision Making Male Middle Aged Diagnosis, Computer-Assisted Aged, 80 and over Adult
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Virtual to Real Adaptation of Pedestrian Detectors.

Sensors (Basel, Switzerland) Sep 14, 2020
Pedestrian detection through Computer Vision is a building block for a multitude of applications. Recently, there has been an increasing interest in convolutional neural network-based architectures to execute such a task. One of these supervised netw...
Movement Pedestrians Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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Review of medical image recognition technologies to detect melanomas using neural networks.

BMC bioinformatics Sep 14, 2020
BACKGROUND: Melanoma is one of the most aggressive types of cancer that has become a world-class problem. According to the World Health Organization estimates, 132,000 cases of the disease and 66,000 deaths from malignant melanoma and other forms of ...
Humans Melanoma Skin Neoplasms Melanoma, Cutaneous Malignant Data Accuracy Image Interpretation, Computer-Assisted Deep Learning Early Detection of Cancer Sensitivity and Specificity
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