Title:
Acoustic Imaging of Bruises

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prabhakara_sandeep_200608_mast.pdf (2.03 MB)
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Prabhakara, Sandeep
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Sprigle, Stephen
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http://hdl.handle.net/1853/11501
Abstract
Ultrasound is a valuable tool to monitor wound healing. In this report, ultrasound is used to determine the features in the B-scans that correspond to a bruise. High frequency ultrasound scans show clear and distinct features that correspond to a laceration or a late stage pressure ulcer. This is because of the extensive damage and the rupture of the epidermis in both the cases. This study assumes significance because it is an effort to find such artifacts in the ultrasound scans of bruises caused by blunt forces where the epidermis remains intact. In this study, the structure of the skin was visualized using a 20 MHz ultrasound scanner. Skin thickness and echogenicity changes may result due to blood extravasations or edema. The thickness and the echogenicity values are plotted against time to determine the trend in the variation of these parameters. We see an intraday and a daily fluctuation of skin thickness and echogenicity albeit with no distinct trend on a day to day basis or between subjects. The results also give us a good estimation of the variation observable in these parameters in the event of an injury. A snapshot analysis is also performed, which describes qualitatively the structural changes in the B-scan of the bruise site compared to the control site. There are six different types of qualitative changes which can appear in the B-scan of a bruised site compared to the control. In the event of an injury, usually, more than one of these changes is manifested in the scan of a bruise. Skin thickness and echogenicity vary considerably due to a number of physiological factors which can seldom be controlled. Therefore, these parameters can give conclusive evidence of a bruise only if the change between a bruised region and a control region is much greater than the daily, normal variations. Snapshot analysis can help detect a bruise or a deep tissue injury. Further work involves the application of pattern recognition or face recognition algorithms to automate the detection.
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2006-05-22
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