Real-time interpolation for true 3-dimensional ultrasound image volumes

Development of an inline inspection robot for the detection of pipeline defects

Purpose

The purpose of this study is to develop a robot for non-destructive testing of the pipelines to improve its reliability and reduce the loss of products due to cracks, corrosions, etc.

Design/methodology/approach

In this study, an inline inspection robot was developed for crack and corrosion detection in the pipeline. The developed robot consists of ultrasonic sensors to avoid obstacles, a visual aid with high resolution to view real time images and colour sensors for corrosion detection. The Autodesk inventor software was used for the drafting and solid modelling of the robot. A dummy pipe of 500 mm diameter and 2,000 mm length with induced cracks and corrosion was fabricated to test the robot. The colour sensors placed at each side of the robot were used to detect corrosion in the dummy pipe whilst the image processing was done to analyse the crack, as well as the type and depth of corrosion present in the dummy pipe.

Findings

The results obtained show the ability of the developed robot to detect cracks and determine the crack growth in the pipeline in addition to its ability to determine corrosion.

Practical implications

Hence, the study provides a diagnostic tool for detecting pipeline defects and analysing the extent of defects to determine the fatigue rate and the useful life of the pipeline.

Originality/value

The novelties of this study is based on the fact that it was designed to avoid obstacles and check for cracks, leakage and corrosion in pipelines autonomously. It has visual aid that makes it possible to see the interior of the pipe. This makes it easier to identify the defect and the location of the defects before a catastrophic failure. The device is also equipped with sensors, which can detect defects and send the signal to a control system, as well as a Bluetooth device so the operator can have real time information about the state and integrity of the pipelines. The system is also integrated with a Bluetooth device, which permits its compatibility with Android and other mobile applications. Thus, the enabled user can send a command to query the state of the pipeline at any location with the feedback received in the form of short message service. Hence, this study offers contribution in the development of an independent (self-governing) system with the capability to autonomously detect defects in pipe walls and effectively communicate feedback to the authorised users. The prototype model for the evaluation of pipeline integrity will bring about a more proactive way to detect pipeline defects so that effort can be geared towards its restoration before it becomes a major problem, which will subsequently affect productivity and incur losses.

Web-Based GPU-Accelerated Application for Multiplanar Reconstructions from Conventional 2D Ultrasound

PURPOSE

 In ultrasound education there is a need for interactive web-based learning resources. The purpose of this project was to develop a web-based application that enables the generation and exploration of volumetric datasets from cine loops obtained with conventional 2D ultrasound.

MATERIALS AND METHODS

 JavaScript code for ultrasound video loading and the generation of volumetric datasets was created and merged with an existing web-based imaging viewer based on JavaScript and HTML5. The Web Graphics Library was utilized to enable hardware-accelerated image rendering.

RESULTS

 The result is a web application that works in most major browsers without any plug-ins. It allows users to load a conventional 2D ultrasound cine loop which can subsequently be manipulated with on-the-fly multiplanar reconstructions as in a Digital Imaging and Communications in Medicine (DICOM) viewer. The application is freely accessible at (http://www.castlemountain.dk/atlas/index.php?page=mulrecon&mulreconPage=sonoviewer) where a demonstration of web-based sharing of generated cases can also be found.

CONCLUSION

 The developed web-based application is unique in its ability to easily perform loading of one's own ultrasound clips and conduct multiplanar reconstructions where interactive cases can be shared on the Internet.

Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases

OBJECT

Fiducial-based registration (FBR) is used widely for patient registration in image-guided neurosurgery. The authors of this study have developed an automatic fiducial-less registration (FLR) technique to find the patient-to-image transformation by directly registering 3D ultrasound (3DUS) with MR images without incorporating prior information. The purpose of the study was to evaluate the performance of the FLR technique when used prospectively in the operating room and to compare it with conventional FBR.

METHODS

In 32 surgical patients who underwent conventional FBR, preoperative T1-weighted MR images (pMR) with attached fiducial markers were acquired prior to surgery. After craniotomy but before dural opening, a set of 3DUS images of the brain volume was acquired. A 2-step registration process was executed immediately after image acquisition: 1) the cortical surfaces from pMR and 3DUS were segmented, and a multistart sum-of-squared-intensity-difference registration was executed to find an initial alignment between down-sampled binary pMR and 3DUS volumes; and 2) the alignment was further refined by a mutual information-based registration between full-resolution grayscale pMR and 3DUS images, and a patient-to-image transformation was subsequently extracted.

RESULTS

To assess the accuracy of the FLR technique, the following were quantified: 1) the fiducial distance error (FDE); and 2) the target registration error (TRE) at anterior commissure and posterior commissure locations; these were compared with conventional FBR. The results showed that although the average FDE (6.42 ± 2.05 mm) was higher than the fiducial registration error (FRE) from FBR (3.42 ± 1.37 mm), the overall TRE of FLR (2.51 ± 0.93 mm) was lower than that of FBR (5.48 ± 1.81 mm). The results agreed with the intent of the 2 registration techniques: FBR is designed to minimize the FRE, whereas FLR is designed to optimize feature alignment and hence minimize TRE. The overall computational cost of FLR was approximately 4-5 minutes and minimal user interaction was required.

CONCLUSIONS

Because the FLR method directly registers 3DUS with MR by matching internal image features, it proved to be more accurate than FBR in terms of TRE in the 32 patients evaluated in this study. The overall efficiency of FLR in terms of the time and personnel involved is also improved relative to FBR in the operating room, and the method does not require additional image scans immediately prior to surgery. The performance of FLR and these results suggest potential for broad clinical application.

Intraoperative patient registration using volumetric true 3D ultrasound without fiducials

PURPOSE

Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images.

METHODS

Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations.

RESULTS

In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable).

CONCLUSIONS

Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.