Works (3)

Updated: July 5th, 2023 15:54

2013 journal article

Acoustic Radiation Force Beam Sequence Performance for Detection and Material Characterization of Atherosclerotic Plaques: Preclinical, Ex Vivo Results

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 60(12), 2471–2487.

MeSH headings : Algorithms; Animals; Elasticity Imaging Techniques / methods; Femoral Artery / diagnostic imaging; Femoral Artery / pathology; Image Processing, Computer-Assisted; Phantoms, Imaging; Plaque, Atherosclerotic / diagnostic imaging; ROC Curve; Swine
TL;DR: Results suggest ARF-based imaging is relevant to detecting and characterizing plaques and support its use for diagnosing and monitoring atherosclerosis. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2009 journal article

ARFI IMAGING FOR NONINVASIVE MATERIAL CHARACTERIZATION OF ATHEROSCLEROSIS PART II: TOWARD IN VIVO CHARACTERIZATION

ULTRASOUND IN MEDICINE AND BIOLOGY, 35(2), 278–295.

By: R. Behler n, T. Nichols*, H. Zhu*, E. Merricks* & C. Gallippi n

author keywords: Acoustic radiation force; Ultrasound; Atherosclerosis; Detection; Characterization; Collagen; Elastin; Pig model
MeSH headings : Acoustics; Algorithms; Animals; Atherosclerosis / diagnostic imaging; Collagen / analysis; Elastin / analysis; Iliac Artery / diagnostic imaging; Image Interpretation, Computer-Assisted / methods; Immunohistochemistry; Models, Animal; Swine; Ultrasonography
TL;DR: Acoustic radiation force impulse (ARFI) ultrasound, a novel imaging method for noninvasively differentiating the mechanical properties of tissue, is demonstrated for in vivo detection of nonstenotic plaques and plaque material assessment in this pilot investigation, validates the potential relevance of ARFI imaging as a noninvasive imaging technology for in vitro detection and material assessment of atherosclerotic plaque. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2008 journal article

Robust principal component analysis and clustering methods for automated classification of tissue response to ARFI excitation

ULTRASOUND IN MEDICINE AND BIOLOGY, 34(2), 309–325.

By: F. Mauldin n, H. Zhu*, R. Behler n, T. Nichols* & C. Gallippi n

author keywords: acoustic radiation force impulse ultrasound; automatic classification; atherosclerosis; robust principal component analysis; robust K-means clustering
MeSH headings : Acoustics; Algorithms; Animals; Computer Simulation; Iliac Artery / diagnostic imaging; Iliac Artery / metabolism; Image Interpretation, Computer-Assisted / methods; Immunohistochemistry; Principal Component Analysis; Swine; Ultrasonography
TL;DR: This work suggests that automatic identification of tissue structures exhibiting similar displacement responses to ARFI excitation is possible, even in the context of outlier profiles, and represents an important first step toward automatic correlation of ARFI data to spatially matched immunohistochemistry. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

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