AIMC Topic: Image Interpretation, Computer-Assisted

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The Path to and Impact of Disease Recognition with AI.

IEEE pulse Jan 1, 2020
The Process of rare disease identification by clinical geneticists is closely associated with the ability to correlate the phenotype of a patient with the relevant genetic syndromes. In order to perform this correlation, the phenotype has to be descr...
Humans Artificial Intelligence Face Rare Diseases Precision Medicine Genomics Syndrome Image Interpretation, Computer-Assisted
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Deep Learning Technique for Musculoskeletal Analysis.

Advances in experimental medicine and biology Jan 1, 2020
Advancements in musculoskeletal analysis have been achieved by adopting deep learning technology in image recognition and analysis. Unlike musculoskeletal modeling based on computational anatomy, deep learning-based methods can obtain muscle informat...
Muscle, Skeletal Image Interpretation, Computer-Assisted Bone and Bones Tomography, X-Ray Computed Humans Deep Learning
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Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.

Advances in experimental medicine and biology Jan 1, 2020
For computer-aided diagnosis (CAD), detection, segmentation, and classification from medical imagery are three key components to efficiently assist physicians for accurate diagnosis. In this chapter, a completely integrated CAD system based on deep l...
Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Humans Deep Learning Breast Neoplasms Mammography
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Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation.

Advances in experimental medicine and biology Jan 1, 2020
Image-based computer-aided diagnosis (CAD) algorithms by the use of convolutional neural network (CNN) which do not require the image-feature extractor are powerful compared with conventional feature-based CAD algorithms which require the image-featu...
Deep Learning Lung Diseases Image Interpretation, Computer-Assisted Lung Diagnosis, Computer-Assisted Humans
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Deep Learning in Medical Image Analysis.

Advances in experimental medicine and biology Jan 1, 2020
Deep learning is the state-of-the-art machine learning approach. The success of deep learning in many pattern recognition applications has brought excitement and high expectations that deep learning, or artificial intelligence (AI), can bring revolut...
Humans Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted Deep Learning Diagnostic Imaging
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Convolutional Neural Network-based MR Image Analysis for Alzheimer's Disease Classification.

Current medical imaging reviews Jan 1, 2020
BACKGROUND: In this study, we used a convolutional neural network (CNN) to classify Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal control (NC) subjects based on images of the hippocampus region extracted from magnetic resonanc...
Datasets as Topic Case-Control Studies Image Interpretation, Computer-Assisted Cognitive Dysfunction Hippocampus Brain Mapping Alzheimer Disease Magnetic Resonance Imaging Humans Neural Networks, Computer
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Knee Meniscus Segmentation and Tear Detection from MRI: A Review.

Current medical imaging reviews Jan 1, 2020
BACKGROUND: Automatic diagnostic systems in medical imaging provide useful information to support radiologists and other relevant experts. The systems that help radiologists in their analysis and diagnosis appear to be increasing.
Artificial Intelligence Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted Tibial Meniscus Injuries Magnetic Resonance Imaging Humans
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Use of artificial intelligence in imaging in rheumatology - current status and future perspectives.

RMD open Jan 1, 2020
After decades of basic research with many setbacks, artificial intelligence (AI) has recently obtained significant breakthroughs, enabling computer programs to outperform human interpretation of medical images in very specific areas. After this shock...
Machine Learning Deep Learning Arthritis, Rheumatoid Humans Artificial Intelligence Scleroderma, Systemic Rheumatology Magnetic Resonance Imaging Image Interpretation, Computer-Assisted
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An Intelligent Future for Medical Imaging: A Market Outlook on Artificial Intelligence for Medical Imaging.

Journal of the American College of Radiology : JACR Jan 1, 2020
Radiologists today are under increasing work pressure. We surveyed radiologists in the United States across practice settings, and the overwhelming majority reported an increased workload. Artificial intelligence (AI), which includes machine learning...
Humans Cloud Computing Investments Artificial Intelligence Image Processing, Computer-Assisted Attitude to Computers Diagnostic Imaging Forecasting Image Interpretation, Computer-Assisted
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Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: a pilot study.

Abdominal radiology (New York) Jan 1, 2020
PURPOSE: To develop a deep convolutional neural network (CNN) model to categorize multiphase CT and MRI liver observations using the liver imaging reporting and data system (LI-RADS) (version 2014).
Pilot Projects Magnetic Resonance Imaging Liver Tomography, X-Ray Computed Reproducibility of Results Datasets as Topic Liver Diseases Radiology Information Systems Feasibility Studies Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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