
doi: 10.1115/1.3138561
pmid: 3908816
Ultrasonic imaging has become increasingly important as a diagnostic tool in medicine because it is noninvasive and it can provide valuable information otherwise unattainable. However, at present, clinical interpretation of an ultrasonic image still mostly relies on recognition of boundaries and positional relationship of anatomical structures and a subjective analysis of the distribution or texture of echo amplitudes. Other potentially useful information carried back by the echoes is completely discarded. The aim of ultrasonic tissue characterization research is to develop methods to extract additional information from the returned echoes so that tissue pathology or abnormality can be reliably identifed and severity of the pathology objectively assessed with quantiative criteria. A number of ultrasonic parameters including acoustic velocity, impedance, attentuation and scattering, have been utilized in attempting to achieve this goal. In this paper, recent progress in this research will be discussed and relevant results presented.
Organ Specificity, Biomedical Engineering, Animals, Humans, Cattle, Acoustics, Rats, Ultrasonography
Organ Specificity, Biomedical Engineering, Animals, Humans, Cattle, Acoustics, Rats, Ultrasonography
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
