With this paper we present a new approach to calculate 2D strain through the sign up of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid sign up algorithm (INRA). and CNS ideals of the INRA method were much higher than those determined from your CC-based method. Furthermore the medical feasibility of our approach was shown with the data from individuals with arm lymphedema. at level c of resolution is defined by each control mesh Φc and the corresponding spline-based transformation and their sum of the regional transformation FFFD is usually defined as to constrain the deformation of the coordinate space. The cost function comprises two competing goals. A user-defined weighting factor τ(0 ≤ τ 1) controls the relative influence of and ultrasound studies using a clinical scanner (SonixTouch Ultrasonix British Columbia Canada). The elastography phantom (Model 059 CIRS) and human hand were scanned using the L14-5/38 linear probe (128 elements) at 10 MHz center frequency. The arm data were acquired using the BPL9-5/55 probe (256 elements) at 6.5 MHz center frequency. For the CC-based method 4 levels from coarse to fine were used. We used τ = 0.01for the cost function and 3×3 grid spaces for our registration-based Dasatinib (BMS-354825) method. This phantom includes several dense masses (lesions). The elasticity (stiffness) of the each dense mass is at least two times greater than the elasticity of the background which has an elastic modulus of 20 kPa ± 5kPa. For Dasatinib (BMS-354825) phantom results we calculate the Dasatinib (BMS-354825) signal-to-noise ratio (SNR) and contrast to noise ratio (CNR) to assess the overall performance of our method according to and are the spatial strain common of the target and background are the spatial strain variance of the target and background and and are the spatial common and variance of a window in the strain image respectively. Figures 1 shows the comparison of the elastography results of the INRA and CC-based methods along the axial direction of the elastography phantom. Dasatinib (BMS-354825) The breast lesion is clearly visualized on the strain and B-mode fusion image of the Dasatinib (BMS-354825) INRA method yet is not clear around the fusion image of the CC-based method. Figure 2 shows the comparison of the elastography results of the INRA and CC-based method along the lateral direction of Rabbit Polyclonal to TAS2R48. the elastography phantom. The breast lesion is still clear around the B-mode and strain fusion image of the INRA method and is not visible around the fusion image of the CC-based method. Compared with the INRA method the CC-based block match has more artifacts in the axial strain image and the breast lesion in phantom almost cannot be seen in lateral strain images. However the INRA method can detect the lesion in both the axial and lateral strain images. Fig. 1 Phantom experiment results – axial direction Fig. 2 Phantom experiment results – lateral Dasatinib (BMS-354825) direction In order to quantitatively compare the INRA method with the traditional CC-based method we used Eq. (9) to calculate the CNR and SNR in the axial and lateral strain images. We captured 90 frames of B-mode images and RF data while the pressure was evenly loaded by the probe. We used the first frame as the reference frame and selected every 10th frame (10th 20 30 40 and etc.) as the floating frames to compare the CNR and SNR under numerous pressure deformations. The region of interest (ROI) 1 shown in Fig. 2 was used as the target. ROIs 2 and 3 were used as the background. ROIs 1 and 2 were used to calculate the CNR in the axial strain images and ROIs 1 and 3 were used to calculate the CNR in the lateral strain images. Figures 3 and ?and44 illustrate the comparison of CNR and SNR between the two methods in the axial and lateral strains at different pressures (frames). Fig. 3 Comparison of the axial and lateral CNR. Fig. 4 Comparison of the axial and lateral SNR. For the both methods the CNR and SNR in the axial strain were higher than the lateral strain. The CNR and SNR at corresponding directions of our INRA method were significantly higher than the CC-based method. The CNRs for both methods at two directional strains finally decreased along the pressure (deformation) increase while the SNRs increased along the pressure increase. The INRA method was better than the CC-based method in the CNR and SNR. In particular the proposed INRA method can work well under high pressure and large deformation. In the study the CC-based method failed due to the large.