| Budget Amount *help |
¥2,700,000 (Direct Cost: ¥2,700,000)
Fiscal Year 1998: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1997: ¥2,100,000 (Direct Cost: ¥2,100,000)
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| Research Abstract |
The variation of elastic properties of tissues have much relation to the pathological condition. Therefore, the image of strain distribution when static compression is applied are proven to be useful for detecting the disease tissue based on the difference of tissue elastic properties though it is more qualitative but easier to detect than elastic modulus distribution.
So far, many approaches to obtain strain image from echo signals have been proposed. However, most methods are based on the spatial correlation technique and do not suit for real-time processing since they require much computation time. Although alternative approach, that is, a phase tracking method can realize the rapid detection of strain, it does not work a large displacement required for the high SN ratio of strain image. Therefore, we developed a new technique for tissue elasticity imaging from the viewpoint of the feasibility. The proposed approach referred to as the combined autocorrelation method has a merit of ob
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taining high quality strain image with real-time processing and being applicable to a large displacement.
On the other hand, some approach for elasticity imaging are investigated for the purpose of obtaining more quantitative properties of tissues. However, in order to simplify the estimation problem, many approaches for estimating elastic modulus distribution.are based on 2-D model, for example, plane stress distribution or plane strain distribution, which is not always satisfied for actual tissues. Therefore, we have developed a method of estimating the elastic modulus under more practical conditon based on a 3-D tissue model.
Numeric simulation and phantom experiment demonstrated that the method has a higher capability of reconstructing the image of tissue strain distribution in practical condition as compared with conventional spatial correlation method. Moreover, image of elastic modulus distribution was also obtained by estimating stress distribution using 3-D.tissue model. Measurement of breast tumor specimen is performed by the proposed method so that the obtained strain image clearly detected the harder tumor lesions which were vague in B-mode image. Moreover, the results indicated the possibility of extracting the pathological characteristic of tumor to be useful for discrimination of tumor type. These validate the feasibility of the proposed method for clinical application. Less
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