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This paper presents a new needle detection technique for ultrasound guided interventions based on the spectral properties of small displacements arising from hand tremour or intentional motion. In a block-based approach, the displacement map is computed for each block of interest versus a reference frame, using an optical flow technique. To compute the flow parameters, the Lucas-Kanade approach is used in a multiresolution and regularized form. A least-squares fit is used to estimate the flow parameters from the overdetermined system of spatial and temporal gradients. Lateral and axial components of the displacement are obtained for each block of interest at consecutive frames. Magnitude-squared spectral coherency is derived between the median displacements of the reference block and each block of interest, to determine the spectral correlation. In vivo images were obtained from the tissue near the abdominal aorta to capture the extreme intrinsic body motion and insertion images were captured from a tissue-mimicking agar phantom. According to the analysis, both the involuntary and intentional movement of the needle produces coherent displacement with respect to a reference window near the insertion site. Intrinsic body motion also produces coherent displacement with respect to a reference window in the tissue; however, the coherency spectra of intrinsic and needle motion are distinguishable spectrally. Blocks with high spectral coherency at high frequencies are selected, estimating a channel for needle trajectory. The needle trajectory is detected from locally thresholded absolute displacement map within the initial estimate. Experimental results show the RMS localization accuracy of 1:0 mm , 0:7 mm , and 0:5 mm for hand tremour, vibrational and rotational needle movements, respectively. |
