The statistical nature of the echo from the tissue will be analyzed to extract characteristic parameters that will be used to classify the tissue as 'normal' or 'abnormal' and thus enhance chances of correct identification of benign and malignant tumors. The research will be undertaken using the patient data supplied by the clinical core group from Thomas Jefferson University. The techniques developed through this research will therefore be used to propose strategies for the screening of patients for cancer (breast, liver, kidney and prostate) by examining the ultrasound B-scans. It is hoped that outcomes of this research will be such that a low cost simpler method could be developed for the screening of patients for cancer using ultrasound, a nonionizing radiation. A set of criteria will be developed for the classification and identification of tumors, based on the generalized non-Rayleigh statistics of the backscattered echo. The amplitude as well as the phase information of the backscattered and quadrature demodulated echo will be utilized towards the primary goal of tissue classification. Quantities such as moments, correlation and characteristic parameters of the K distribution will be extracted from the data supplied by the clinical core. These will be used to classify the tissue as well as localize the abnormality (tumor) on the basis of the criteria to be developed. In addition, the information generated will be utilized for improving the detectability of tumors in the ultrasonic B scans of the organs. Finally new algorithms will be developed to suppress the unwanted signal generated by the intervening tissue and to improve the detection and identification of tumors.
| Wheatley, Margaret A; Forsberg, Flemming; Oum, Kelleny et al. (2006) Comparison of in vitro and in vivo acoustic response of a novel 50:50 PLGA contrast agent. Ultrasonics 44:360-7 |
| Wheatley, Margaret A; Forsberg, Flemming; Dube, Neal et al. (2006) Surfactant-stabilized contrast agent on the nanoscale for diagnostic ultrasound imaging. Ultrasound Med Biol 32:83-93 |
| Mogatadakala, Kishore V; Donohue, Kevin D; Piccoli, Catherine W et al. (2006) Detection of breast lesion regions in ultrasound images using wavelets and order statistics. Med Phys 33:840-9 |
| Shankar, P M; Piccoli, C W; Reid, J M et al. (2005) Application of the compound probability density function for characterization of breast masses in ultrasound B scans. Phys Med Biol 50:2241-8 |
| Forsberg, Flemming; Lathia, Justin D; Merton, Daniel A et al. (2004) Effect of shell type on the in vivo backscatter from polymer-encapsulated microbubbles. Ultrasound Med Biol 30:1281-7 |
| El-Sherif, Dalia M; Lathia, Justin D; Le, Ngocyen T et al. (2004) Ultrasound degradation of novel polymer contrast agents. J Biomed Mater Res A 68:71-8 |
| Alacam, Burak; Yazici, Birsen; Bilgutay, Nihat et al. (2004) Breast tissue characterization using FARMA modeling of ultrasonic RF echo. Ultrasound Med Biol 30:1397-407 |
| Lathia, Justin D; Leodore, Lauren; Wheatley, Margaret A (2004) Polymeric contrast agent with targeting potential. Ultrasonics 42:763-8 |
| Oeffinger, Brian E; Wheatley, Margaret A (2004) Development and characterization of a nano-scale contrast agent. Ultrasonics 42:343-7 |
| Shankar, P Mohana; Dumane, Vishruta A; Piccoli, Catherine W et al. (2003) Computer-aided classification of breast masses in ultrasonic B-scans using a multiparameter approach. IEEE Trans Ultrason Ferroelectr Freq Control 50:1002-9 |
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