AIMC Topic:
Image Interpretation, Computer-Assisted
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Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging.
Breast cancer research and treatment
Feb 4, 2020
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological mean...
Domain-invariant interpretable fundus image quality assessment.
Medical image analysis
Jan 30, 2020
Objective and quantitative assessment of fundus image quality is essential for the diagnosis of retinal diseases. The major factors in fundus image quality assessment are image artifact, clarity, and field definition. Unfortunately, most of existing ...
Neural-network-based Motion Tracking for Breast Ultrasound Strain Elastography: An Initial Assessment of Performance and Feasibility.
Ultrasonic imaging
Jan 30, 2020
Accurate tracking of tissue motion is critically important for several ultrasound elastography methods. In this study, we investigate the feasibility of using three published convolution neural network (CNN) models built for optical flow (hereafter r...
Artificial Intelligence in Radiology Residency Training.
Seminars in musculoskeletal radiology
Jan 28, 2020
Artificial intelligence (AI) is an emerging technology that brings a wide array of new tools to the field of radiology. AI will certainly have an impact on the day-to-day work of radiologists in the coming decades, thus training programs must prepare...
From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.
Seminars in musculoskeletal radiology
Jan 28, 2020
The radiology practice has access to a wealth of data in the radiologist information system, dictation reports, and electronic health records. Although many artificial intelligence applications in radiology have focused on computer vision and the int...
Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics.
Seminars in musculoskeletal radiology
Jan 28, 2020
Although still limited in clinical practice, quantitative analysis is expected to increase the value of musculoskeletal (MSK) imaging. Segmentation aims at isolating the tissues and/or regions of interest in the image and is crucial to the extraction...
Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence.
Seminars in musculoskeletal radiology
Jan 28, 2020
Artificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect a...
The Use of Artificial Intelligence in the Evaluation of Knee Pathology.
Seminars in musculoskeletal radiology
Jan 28, 2020
Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic ev...
Improving the Speed of MRI with Artificial Intelligence.
Seminars in musculoskeletal radiology
Jan 28, 2020
Magnetic resonance imaging (MRI) is a leading image modality for the assessment of musculoskeletal (MSK) injuries and disorders. A significant drawback, however, is the lengthy data acquisition. This issue has motivated the development of methods to ...
Artificial Intelligence Explained for Nonexperts.
Seminars in musculoskeletal radiology
Jan 28, 2020
Artificial intelligence (AI) has made stunning progress in the last decade, made possible largely due to the advances in training deep neural networks with large data sets. Many of these solutions, initially developed for natural images, speech, or t...
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