Ultrasound Imaging in Vascular Diseases

Fragou, Mariantina; Karabinis, Andréas; Daphnis, Eugene; Labropoulos, N; Karakitsos, Dimitrios

doi:10.5772/19236

Cited by 1 publication

(2 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ultrasound imaging has become one of the most important modalities used in the assessment of vascular diseases. Virtually all peripheral arterial and venous structures can be visualized with the duplex ultrasound (DU), which currently is the main diagnostic modality used in deep venous thrombosis and carotid disease (Fragou et al 2011). For carotid artery disease, the carotid plaque is traditionally judged according to the degree of stenosis and a 70% or greater diameter loss is an indication for surgery.…”

Section: Vascular Diseasementioning

confidence: 99%

“…In the era of atherosclerosis, intravascular ultrasound (IVUS), a catheter-based imaging technique, has evolved as a valuable technique for diagnosis and intervention for coronary disease, by providing more precise measurement on intimal thickness and vulnerable plaques. In contrast, angiography, the traditionally used "gold-standard" in the imaging of vascular morphology, can only depict contrast agent filled lumen and not the vessel wall (Fragou et al 2011). IVUS provides images of vascular structure by scanning inside the vessel, which are acquired by a mechanically rotated transducer or a multi-element transducer array.…”

Section: Vascular Diseasementioning

confidence: 99%

See 1 more Smart Citation

Ultrasound tissue classification: a review

et al. 2020

View full text Add to dashboard Cite

Ultrasound imaging is the most widespread medical imaging modality for creating images of the human body in clinical practice. Tissue classification in ultrasound has been established as one of the most active research areas, driven by many important clinical applications. In this paper, we present a survey on ultrasound tissue classification, focusing on recent advances in this area. We start with a brief review on the main clinical applications. We then introduce the traditional approaches, where the existing research on feature extraction and classifier design are reviewed. As deep learning approaches becoming popular for medical image analysis, the recent deep learning methods for tissue classification are also introduced. We briefly discuss the FDA-cleared techniques being used clinically. We conclude with the discussion on the challenges and research focus in future.

show abstract

Section: Vascular Diseasementioning

confidence: 99%

Section: Vascular Diseasementioning

confidence: 99%