Effect of lithotripter focal width on stone comminution in shock wave lithotripsy.

Using a reflector insert, the original HM-3 lithotripter field at 20 kV was altered significantly with the peak positive pressure (p(+)) in the focal plane increased from 49 to 87 MPa while the -6 dB focal width decreased concomitantly from 11 to 4 mm. Using the original reflector, p(+) of 33 MPa with a -6 dB focal width of 18 mm were measured in a pre-focal plane 15-mm proximal to the lithotripter focus. However, the acoustic pulse energy delivered to a 28-mm diameter area around the lithotripter axis was comparable ( approximately 120 mJ). For all three exposure conditions, similar stone comminution ( approximately 70%) was produced in a mesh holder of 15 mm after 250 shocks. In contrast, stone comminution produced by the modified reflector either in a 15-mm finger cot (45%) or in a 30-mm membrane holder (14%) was significantly reduced from the corresponding values (56% and 26%) produced by the original reflector (no statistically significant differences were observed between the focal and pre-focal planes). These observations suggest that a low-pressure/broad focal width lithotripter field will produce better stone comminution than its counterpart with high-pressure/narrow focal width under clinically relevant in vitro comminution conditions.

Recognition of Planar Segments in Point Cloud Based on Wavelet Transform

© 2005-2012 IEEE.Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies.