AIMC Topic:
Ultrasonography
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The use of artificial neural network analysis can improve the risk-stratification of patients presenting with suspected deep vein thrombosis.
British journal of haematology
Feb 6, 2019
Artificial neural networks are machine-learning algorithms designed to analyse data without a pre-existing hypothesis as to any associations that may exist. This technique has not previously been applied to the risk stratification of patients referre...
Gain determination of feedback force for an ultrasound scanning robot using genetic algorithm.
International journal of computer assisted radiology and surgery
Feb 1, 2019
PURPOSE: The remote medical diagnosis system (RMDS) is for providing medical diagnosis to the patients located in remote sites. To apply to RMDS and medical automation, many master-slave type ultrasound scanning robots are being developed and researc...
Rheumatoid Arthritis: Atherosclerosis Imaging and Cardiovascular Risk Assessment Using Machine and Deep Learning-Based Tissue Characterization.
Current atherosclerosis reports
Jan 25, 2019
PURPOSE OF THE REVIEW: Rheumatoid arthritis (RA) is a chronic, autoimmune disease which may result in a higher risk of cardiovascular (CV) events and stroke. Tissue characterization and risk stratification of patients with rheumatoid arthritis are a ...
Breast mass classification in sonography with transfer learning using a deep convolutional neural network and color conversion.
Medical physics
Jan 16, 2019
PURPOSE: We propose a deep learning-based approach to breast mass classification in sonography and compare it with the assessment of four experienced radiologists employing breast imaging reporting and data system 4th edition lexicon and assessment p...
Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network.
World journal of surgical oncology
Jan 8, 2019
BACKGROUND: In this study, images of 2450 benign thyroid nodules and 2557 malignant thyroid nodules were collected and labeled, and an automatic image recognition and diagnosis system was established by deep learning using the YOLOv2 neural network. ...
Feasibility of a Support Vector Machine Classifier for Myofascial Pain Syndrome: Diagnostic Case-Control Study.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jan 7, 2019
OBJECTIVES: Myofascial pain syndrome (MPS) is the most common cause of chronic pain worldwide. The diagnosis of MPS is subjective, which has created a need for a robust quantitative method of diagnosing MPS. We propose that using a support vector mac...
Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound.
Journal of visualized experiments : JoVE
Jan 7, 2019
With the potential for high precision, dexterity, and repeatability, a self-tracked robotic system can be employed to assist the acquisition of real-time ultrasound. However, limited numbers of robots designed for extra-corporeal ultrasound have been...
Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study.
The Lancet. Oncology
Dec 21, 2018
BACKGROUND: The incidence of thyroid cancer is rising steadily because of overdiagnosis and overtreatment conferred by widespread use of sensitive imaging techniques for screening. This overall incidence growth is especially driven by increased diagn...
Quantitative ultrasound and machine learning for assessment of steatohepatitis in a rat model.
European radiology
Dec 17, 2018
OBJECTIVES: To develop a machine learning model based on quantitative ultrasound (QUS) parameters to improve classification of steatohepatitis with shear wave elastography in rats by using histopathology scoring as the reference standard.
Deep embeddings for novelty detection in myopathy.
Computers in biology and medicine
Dec 11, 2018
We address the challenge of finding anomalies in ultrasound images via deep learning, specifically applying this to screening for myopathies and finding rare presentations of myopathic disease. Among myopathic diseases, this study focuses on the use ...
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