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contributor authorK. Mala
contributor authorV. Sadasivam
contributor authorS. Alagappan
date accessioned2017-05-09T00:25:18Z
date available2017-05-09T00:25:18Z
date copyrightJune, 2007
date issued2007
identifier issn1932-6181
identifier otherJMDOA4-27984#180_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/136590
description abstractThe use of ultrasonography as an imaging modality has become widespread because of its ability to visualize the organs with no deleterious effects and low cost. Using ultrasonic liver images focal diseases can be identified by differences in echogenicity between normal and areas affected by diseases. In the presence of diffused disease, however, the entire organ may be affected. In that situation, there is no contrast in echo intensity on which to base a diagnosis. Hence it is difficult for an experienced clinician to diagnose the diffused liver diseases by simple visual interpretations. This can be improved by providing useful information, obtained by computer aided tissue characterization, that cannot be obtained by simple visual interpretation.
publisherThe American Society of Mechanical Engineers (ASME)
titleCombined Statistical and Multiscale View on Ultrasonic Liver Images for Characterization
typeJournal Paper
journal volume1
journal issue2
journal titleJournal of Medical Devices
identifier doi10.1115/1.2735975
journal fristpage180
journal lastpage184
identifier eissn1932-619X
keywordsLiver
keywordsWavelets
keywordsArtificial neural networks AND Design
treeJournal of Medical Devices:;2007:;volume( 001 ):;issue: 002
contenttypeFulltext


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