Single 3D Scan Research Articles

Multipathway multi‐echo (MPME) imaging: all main MR parameters mapped based on a single 3D scan

Quantitative parameter maps, as opposed to qualitative grayscale images, may represent the future of diagnostic MRI. A new quantitative MRI method is introduced here that requires a single 3D acquisition, allowing good spatial coverage to be achieved in relatively short scan times. A multipathway multi-echo sequence was developed, and at least 3 pathways with 2 TEs were needed to generate T1 , T2 , T2 * , B1 + , and B0 maps. The method required the central k-space region to be sampled twice, with the same sequence but with 2 very different nominal flip angle settings. Consequently, scan time was only slightly longer than that of a single scan. The multipathway multi-echo data were reconstructed into parameter maps, for phantom as well as brain acquisitions, in 5 healthy volunteers at 3 T. Spatial resolution, matrix size, and FOV were 1.2 × 1.0 × 1.2 mm3 , 160 × 192 × 160, and 19.2 × 19.2 × 19.2 cm3 (whole brain), acquired in 11.5 minutes with minimal acceleration. Validation was performed against T1 , T2 , and T2 * maps calculated from gradient-echo and spin-echo data. In Bland-Altman plots, bias and limits of agreement for T1 and T2 results in vivo and in phantom were -2.9/±125.5 ms (T1 in vivo), -4.8/±20.8 ms (T2 in vivo), -1.5/±18.1 ms (T1 in phantom), and -5.3/±7.4 ms (T2 in phantom), for regions of interest including given brain structures or phantom compartments. Due to relatively high noise levels, the current implementation of the approach may prove more useful for region of interest-based as opposed to pixel-based interpretation. We proposed a novel approach to quantitatively map MR parameters based on a multipathway multi-echo acquisition.

Three-Dimensional Registration for Handheld Profiling Systems Based on Multiple Shot Structured Light.

In this article, a multi-view registration approach for the 3D handheld profiling system based on the multiple shot structured light technique is proposed. The multi-view registration approach is categorized into coarse registration and point cloud refinement using the iterative closest point (ICP) algorithm. Coarse registration of multiple point clouds was performed using relative orientation and translation parameters estimated via homography-based visual navigation. The proposed system was evaluated using an artificial human skull and a paper box object. For the quantitative evaluation of the accuracy of a single 3D scan, a paper box was reconstructed, and the mean errors in its height and breadth were found to be 9.4 μm and 23 μm, respectively. A comprehensive quantitative evaluation and comparison of proposed algorithm was performed with other variants of ICP. The root mean square error for the ICP algorithm to register a pair of point clouds of the skull object was also found to be less than 1 mm.

Detection of traversable region around a mobile robot by computing terrain unevenness from the range data of a 3D laser scanner

Purpose – The purpose of this paper is to detect traversable regions surrounding a mobile robot by computing terrain unevenness using the range data obtained from a single 3D scan. Design/methodology/approach – The geometry of acquiring range data from a 3D scan is exploited to probe the terrain and extract traversable regions. Nature of terrain under each scan point is quantified in terms of an unevenness value, which is computed from the difference in range of scan point with respect to its neighbours. Both radial and transverse unevenness values are computed and compared with threshold values at every point to determine if the point belongs to a traversable region or an obstacle. A region growing algorithm spreads like a wavefront to join all traversable points into a traversable region. Findings – This simple method clearly distinguishes ground and obstacle points. The method works well even in presence of terrain slopes or when the robot experiences pitch and roll. Research limitations/implications – The method applies on single 3D scans and not on aggregated point cloud in general. Practical implications – The method has been tested on a mobile robot in outdoor environment in our research centre. Social implications – This method, along with advanced navigation schemes, can reduce human intervention in many mobile robot applications including unmanned ground vehicles. Originality/value – Range difference between scan points has been used earlier for obstacle detection, but no methodology has been developed around this concept. The authors propose a concrete method based on computation of radial and transverse unevenness at every point and detecting obstacle edges using range-dependent threshold values.

Scalable wide-field optical coherence tomography-based angiography for in vivo imaging applications.

Recent advances in optical coherence tomography (OCT)-based angiography have demonstrated a variety of biomedical applications in the diagnosis and therapeutic monitoring of diseases with vascular involvement. While promising, its imaging field of view (FOV) is however still limited (typically less than 9 mm2), which somehow slows down its clinical acceptance. In this paper, we report a high-speed spectral-domain OCT operating at 1310 nm to enable wide FOV up to 750 mm2. Using optical microangiography (OMAG) algorithm, we are able to map vascular networks within living biological tissues. Thanks to 2,048 pixel-array line scan InGaAs camera operating at 147 kHz scan rate, the system delivers a ranging depth of ~7.5 mm and provides wide-field OCT-based angiography at a single data acquisition. We implement two imaging modes (i.e., wide-field mode and high-resolution mode) in the OCT system, which gives highly scalable FOV with flexible lateral resolution. We demonstrate scalable wide-field vascular imaging for multiple finger nail beds in human and whole brain in mice with skull left intact at a single 3D scan, promising new opportunities for wide-field OCT-based angiography for many clinical applications.

Accuracy of computer-assisted iliosacral screw placement using a hybrid operating room

IntroductionIn recent years hybrid operating rooms were established all over the world. In our setting we combined a 3D flat-panel c-arm (Artis zeego, Siemens) with a navigation system (BrainLab curve, BrainLab). This worldwide unique combination enables the surgeon to visualise an entire pelvis in CT-like image quality with a single 3D-scan. The aim of our study was to investigate, if utilisation of a hybrid operating room increases the accuracy of SI-screws in comparison to standard 3D-navigation. Material and methodsRetrospective, not randomised single centre case series at a level I trauma centre. Inclusion criterion was insertion of a percutaneous iliosacral screw using image-guidance in the hybrid operating room. 61 patients (35 female, 26 male) were included from June 2012 till October 2014. 65 iliosacral screws were inserted. Intraoperative 3D-scans and postoperative scans were examined to investigate screw placement. The results were compared to a preceding study performed in 2012 using conventional 3D-navigation. Statistical calculations were performed with Microsoft Excel 2011 and SPSS. Results65 iliosacral screws were implanted. Two different types of screws were implanted: 1. “Standard” iliosacral screws stabilizing one joint/a unilateral fracture. 2. Single SI-screws stabilizing both SI-joints and if present a bilateral fracture. Forty one patients were included in group 1 (screws n=45). There was no perforation in 43 screws, grade 1 perforation in 2 screws. There was no grade 2 or 3 perforation in this group. Compared to the conventional 3D-navigated screws there was a highly significant difference (p<0.001). Twenty patients could be included in group 2. Eleven screws showed a complete intraosseous position. There was grade 1 perforation in 2 screws, grade 2 perforation in 5 screws and grade 3 perforation in 2 screws. ConclusionImprovements in image quality and enlargement of the display window lead to better intraoperative visualisation of the entire dorsal pelvis. Thereby the accuracy of computer-assisted iliosacral screws could be increased using a hybrid operating room. Furthermore difficult tasks like a single screw for both joints can be accomplished.

First Year Experience using an Interdisciplinary Hybrid Operating Theater for Spinal Surgery in a Level 1 Trauma Hospital

Introduction An interdisciplinary hybrid operating theater was established in June 2012 at the University of Ulm. A floor-based 3D flat panel robotic C-arm (Artis Zeego, Siemens, Germany) is connected to the operating table and the ceiling-based navigation system (BrainLab Curve, BrainLab, Germany). The robotic C-arm is controlled by the surgeon through a control panel mounted on the operating table in the sterile field. The large field of view of the flat panel C-arm allows visualization of the entire lumbar spine or pelvic ring with a single intraoperative 3D scan. This operating room is shared by four different disciplines (orthopedic surgery, neurosurgery, vascular, and cardiac surgery). This hybrid setup represents an advanced imaging and navigation system, and is the first of its type. Material and Methods We included all orthopedic surgeries performed in the hybrid operating theater during the first year. All the cases were reviewed for postoperative complications. Results A total of 92 cases in 91 patients were performed in the first year. Posterior stabilization of the spine was the most common procedure (57.6%) followed by sacroiliac screws (13%). Other procedures included tumor resection of the spine or pelvis, kyphoplasty, and fixation of acetabular and extremity fractures. Overall, 51.1% of the cases used navigation and 46.7% a minimally invasive technique. Complications included four postoperative seroma and two consecutive infections. All seroma and infections occurred in tumor resections. In large tumor resections, two neurological deficits were detected. Another patient developed dysphagia after fixation of an odontoid and atlas fracture. Conclusion None of the complications occurred because of the use of the hybrid operating theater instead of a conventional operating theater. The hybrid operating theater combines high quality, large field intraoperative imaging with advanced navigation. This results in a higher surgeon confidence in hardware placement and total tumor resection. The control panel mounted on the operating table enables the surgeon to operate this complex imaging device in the sterile field. The interdisciplinary use of the operating theater optimizes utilization.

3D ultrasound DICOM data of the thyroid gland

SummaryPurpose: It has recently become possible to generate and archive three-dimensional ultrasound (3D-US) volume data with the DICOM standard Enhanced Ultrasound Volume Storage (EUVS). The objective of this study was to examine the application of the EUVS standard based on the example of thyroid ultrasound. Patients, methods: 32 patients, who were referred for thyroid diagnosis, were given a 3D-US examination of the thyroid gland (GE Voluson E8, convex 3D probe RAB4–8-D). The 3D data sets were exported to EUVS. Necessary additions to DICOM entries and transformation into an established DICOM standard were carried out. The visual assessment and volume measurements were performed by two experts on nuclear medicine using standard software in our hospital. Results: In 24/32 (75%) of the patients, the whole organ was successfully recorded in a single 3D scan; in 8/32 (25%), only part of organ could be covered. In all cases, 3D-US data could be exported and archived. After supplementing the DICOM entry Patient Orientation and transformation into the DICOM PET format, 3D-US data could be displayed in the correct orientation and size at any viewing workstation and any web browser-based PACS viewer. Afterwards, 3D processing such as multiplanar reformation, volumetric measurements and image fusion with data of other cross sectional modalities could be performed. The intraclass correlation of the volume measurements was 0,94 and the interobserver variability was 5.7%. Conclusion: EUVS allows the generation, distribution and archiving of 3D-US data of the thyroid, facilitates a second reading by another physician and creates conditions for advanced 3D processing using routine software

A Layered Approach to People Detection in 3D Range Data

People tracking is a key technology for autonomous systems, intelligent cars and social robots operating in populated environments. What makes the task difficult is that the appearance of humans in range data can change drastically as a function of body pose, distance to the sensor, self-occlusion and occlusion by other objects. In this paper we propose a novel approach to pedestrian detection in 3D range data based on supervised learning techniques to create a bank of classifiers for different height levels of the human body. In particular, our approach applies AdaBoost to train a strong classifier from geometrical and statistical features of groups of neighboring points at the same height. In a second step, the AdaBoost classifiers mutually enforce their evidence across different heights by voting into a continuous space. Pedestrians are finally found efficiently by mean-shift search for local maxima in the voting space. Experimental results carried out with 3D laser range data illustrate the robustness and efficiency of our approach even in cluttered urban environments. The learned people detector reaches a classification rate up to 96% from a single 3D scan.

A Bimodal Laser-Based Attention System

In this paper, we present a new bimodal attention system for robotic applications capable of processing data from different sensor modes simultaneously. Considering several sensor modalities is an obvious approach to regard a variety of object properties. Nevertheless, conventional attention systems only regard the processing of camera images. In contrast to these systems, the input data to our system are provided by a bimodal 3D laser scanner, mounted on top of an autonomous mobile robot. In a single 3D scan pass, the scanner yields range as well as reflectance data. Both data modes are illumination independent, yielding a robust approach that enables all day operation. Data from both laser modes are fed into our attention system built on principles of one of the standard models of visual attention by Koch and Ullman. The system computes conspicuities of both modes in parallel and fuses them into one saliency map. The focus of attention is directed to the most salient points in this map sequentially. We present results on recorded scans of indoor and outdoor scenes showing the respective advantages of the sensor modalities enabling the mode-specific detection of different object properties. Furthermore, we show as an application of the attention system the recognition of objects for building semantic 3D maps of the robot’s environment.