AIMC Topic: Elasticity Imaging Techniques

Clear Filters Showing 101 to 110 of 110 articles

[Reconstruction of elasticity modulus distribution base on semi-supervised neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Accurate reconstruction of tissue elasticity modulus distribution has always been an important challenge in ultrasound elastography. Considering that existing deep learning-based supervised reconstruction methods only use simulated displacement data ...

Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis.

Radiology
Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjective interpretation of US images. Purpose To evaluate the agreement and diagnostic performance of radiologists and a deep learning model in grading hepat...

Feasibility of a Deep Learning approach to estimate Shear Wave Speed using the framework of Reverberant Shear Wave Elastography: A numerical simulation study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Reverberant Shear Wave Elastography (RSWE) is an ultrasound elastography technique that offers great advantages, however, current estimators generate underestimations and time-consuming issues. As well, the involvement of Deep Learning into the medic...

Accurate and generalizable quantitative scoring of liver steatosis from ultrasound images scalable deep learning.

World journal of gastroenterology
BACKGROUND: Hepatic steatosis is a major cause of chronic liver disease. Two-dimensional (2D) ultrasound is the most widely used non-invasive tool for screening and monitoring, but associated diagnoses are highly subjective.

Deep-learning-based approach for strain estimation in phase-sensitive optical coherence elastography.

Optics letters
In this Letter, a deep-learning-based approach is proposed for estimating the strain field distributions in phase-sensitive optical coherence elastography. The method first uses the simulated wrapped phase maps and corresponding phase-gradient maps t...

Learning hidden elasticity with deep neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Elastography is an imaging technique to reconstruct elasticity distributions of heterogeneous objects. Since cancerous tissues are stiffer than healthy ones, for decades, elastography has been applied to medical imaging for noninvasive cancer diagnos...

Emerging technologies in neuromuscular ultrasound.

Muscle & nerve
Neuromuscular ultrasound is an accepted and valuable element in the evaluation of peripheral nerve and muscle disease. However, ultrasound has several limitations to consider, including operator dependency and lack of a viable contrast agent. Fortuna...

A comparison of multimodal biomarkers for chronic hepatitis B assessment using recursive feature elimination.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
An effective assessment of liver fibrosis in patients with chronic hepatitis B (CHB) is highly desired because it is important not only for clinical courses prediction, but also for the determination of antiviral therapy schemes. In recent years, var...