Improvement of Conspicuity by Fusion of Pulse-echo Data

Ultrasonic nondestructive testing based on pulse-echo measurements cannot detect faults if there is no reflected energy. Faults that are hidden behind an obstacle (for instance, another fault), or faults angled along the direction of beam propagation reflect negligible energy and will be difficult to detect. Thus, for a thorough examination of 3-D structures, pulse-echo data is collected from the same location using three different incident angles using different wedges attached to the acoustic probe. Typically, the data from the three wedges, for instance, 0-, 45and 60-degree wedges, are simultaneously collected on three separate channels. The inspector then evaluates the data from all three channels. In this paper, we present a data fusion approach that strategically “fuses” all collected data to improve conspicuity of faults. Obvious advantages of the proposed data fusion are: (1) to visualize occluded faults (if at least one of channel “sees” the fault), (2) the signal-to-noise ratio (SNR) is expected to improve by the factor N where is the number of channels, even by performing a simple averaging as data fusion, and (3) the inspector only has to view one fused data set rather than all the collected data sets. N In particular, the data fusion is applied to the problem of 3-D rendering techniques, namely volume rendering (VR), surface rendering (SR) and maximum intensity projection (MIP). The exact fusion algorithm will differ for different rendering algorithms (SR, VR and MIP) and all will show improved conspicuity for better detection of faults. Introduction: The goal of nondestructive testing is to detect faults (or discontinuities) inside or outside the structure and to evaluate physical and mechanical characteristics without harming it (Bray, 1997). Of various nondestructive testing methods, the ultrasonic pulse-echo method has proved to be effective, especially for metal structures. The pulse-echo ultrasonic system usually provides one or all three display formats: A-, Band C-scan. These displays offer information regarding the nature of the faults, for instance, cracks in metal structures such as pipes and plates. However, only experts trained to interpret A-, B-, or C-scan data is able to detect and locate such faults, especially small miniature cracks. Therefore, to improve conspicuity of faults, we propose a 3-D ultrasonic imaging system based on the pulse-echo measurements to display the data in 3-D, allowing the user to rotate and manipulate the structure. The proposed system gives additional insight since various 3-D views provides additional information that is otherwise unavailable. Furthermore, 3-D views allow users to conveniently locate and measure each faults with greater precision. Providing 3-D views of human anatomy has recently gained popularity in medical community as more patients are scanned volumetrically (usually acquired as a sequence of slice images). As certain imaging protocols will acquire over 100 slice images, volumetric processing and viewing of such data has become a necessity for providing timely diagnosis of patients. Typically, the volumetric data, e.g., a stack of hundreds of images, is processed by one of the following techniques: surface rendering (SR), volume rendering (VR), and maximum intensity projection (MIP) (Roth, 1982; Robb, 1995). The surface rendering technique first extracts the surface to be visualized (usually by a simple threshold) and then, based on the orientation of the surface, the technique renders the surface according to an artificial light source. The volume rendering techniques are mostly based on ray-casting algorithms (Roth, 1982) that paint each pixels on the display according to the voxel values that lie on the ray. The maximum intensity projection also casts rays but selects the maximum intensity on the ray to be painted on the display. These visualization techniques (SR, VR and MIP) mostly have dealt with magnetic resonance images (MRI) and X-ray computed tomographic (CT) images. As for 3-D visualization of medical images using ultrasonic pulse-echo data, various surfaces have been rendered by detecting the interfaces between two tissue types (Capineri, 1996; Prager, 2002), and several similar techniques show promise for imaging various regions of the anatomy, such as articular cartilage (Lefebvre, 1998), prostate (Tong, 1996), and heart (Salustri, 1995). In this paper, we propose a 3-D ultrasonic imaging system that collects and processes multiple pulse-echo data in 3-D for visualization and non-destructive evaluation. We have previously reported some initial results on the MIP technique to visualize the pulse-echo data using MIP (Son, 2002; Song, 2003) as well as the SR and VR (Kwon, 2004). In this paper, we extend our previous results, and propose a technique to fuse the acquired data to improve the conspicuity of faults. Ultrasonic nondestructive testing based on pulse-echo measurements cannot detect faults if there is no reflected energy. Faults that are hidden behind an obstacle (for instance, another fault), or faults angled along the direction of beam propagation reflect negligible energy and will be difficult to detect. Thus, for a thorough examination of 3-D structures, pulse-echo data is collected from the same location using three different incident angles using different wedges attached to the acoustic probe. Typically, the data from the three wedges, for instance, 0-, 45and 60degree wedges, are simultaneously collected on three separate channels. The inspector then evaluates the data from all three channels. In this paper, we present a data fusion approach that strategically “fuses” all collected data to improve conspicuity of faults. Obvious advantages of the proposed data fusion are: (1) to visualize occluded faults (if at least one of channel “sees” the fault), (2) the signal-to-noise ratio (SNR) is expected to improve by the factor N where is the number of channels, even by performing a simple averaging as data fusion, and (3) the inspector only has to view one fused data set rather than all the collected data sets. In particular, the data fusion is applied to the problem of 3-D rendering techniques, namely volume rendering (VR), surface rendering (SR) and maximum intensity projection (MIP). The exact fusion algorithm will differ for different rendering algorithms (SR, VR and MIP) and all will show improved conspicuity for better detection of faults. N Data Acquisition and 3-D Visualization: Figure 1 (a) depicts the pulse-echo data acquisition approach. The transducer is placed on top of the specimen and collects the pulse-echo data moving along the raster scan line. For instance, at one scan line, we acquire one B-scan data from the specimen. The entire B-scan data of the specimen is essentially a sequence of slice images for the specimen. These B-scan data pass through the Wiener filter and the linear interpolator before the 3-D visualization step for the generation of 3-D images. For details see (Song, 2003; Kwon, 2004). Transducer Scan line