Multiple Registration Research Articles

Robust synchronization in SO(3) and SE(3) via low-rank and sparse matrix decomposition

This paper deals with the synchronization problem, which arises in multiple 3D point-set registration and in structure-from-motion. The problem is formulated as a low-rank and sparse matrix decomposition that caters for missing data, outliers and noise, and it benefits from a wealth of available decomposition algorithms that can be plugged-in. A minimization strategy, dubbed R-GoDec, is also proposed. Experimental results on simulated and real data show that this approach offers a good trade-off between resistance to outliers and speed.

Who can tolerate a marginal kidney? Predicting survival after deceased donor kidney transplant by donor-recipient combination.

The impact of donor quality on post-kidney transplant (KT) survival may vary by candidate condition. Characterizing this variation would increase access to KT without sacrificing outcomes. We developed a tool to estimate post-KT survival for combinations of donor quality and candidate condition. We studied deceased donor KT recipients (n=120818) and waitlisted candidates (n=376272) between 2005 and 2016 by using the Scientific Registry of Transplant Recipients. Donor quality and candidate condition were measured by using the Kidney Donor Profile Index (KDPI) and the Estimated Post Transplant Survival (EPTS) score. We estimated 5-year post-KT survival based on combinations of KDPI and EPTS score using random forest algorithms and waitlist survival by EPTS score using Weibull regressions. Survival benefit was defined as absolute reduction in mortality risk with KT. For candidates with an EPTSscore of80, 5-year waitlist survival was 47.6%, and 5-year post-KT survival was 78.9% after receiving kidneys with a KDPIof20 and was 70.7% after receiving kidneys with a KDPIof80. The impact of KDPI on survival benefit varied greatly by EPTS score. For candidates with low EPTS scores (eg, <40), the KDPI had limited impact on survival benefit. For candidates with middle or high EPTS scores (eg, >40), survival benefit decreased with higher KDPI but was still substantial even with a KDPIof100 (>16 percentage points). Our prediction tool (www.transplantmodels.com/kdpi-epts) can support individualized decision-making on kidney offers in clinical practice.

Multiple point sets registration based on Expectation Maximization algorithm

Many methods have been proposed and improved to deal with multi-view point cloud registration. Most of them are based on the classical method, namely Iterative Closest Point(ICP), which is fast and accurate in most cases. However in the presence of noise and outliers, the equal weights ICP assigned to all correspondences would lead to unsatisfactory registration results. To address this issue, this paper proposes a new automatic multi-view registration method based on Expectation Maximization(EM). A Gaussian distribution on representing the relationship between point-sets according to their distance was introduced first. Then EM is brought in to optimize the likelihood function formulated with above Gaussian distribution. Through an iterative method the multi-view registration results can be obtained at last. The experimental results demonstrate accuracy and robustness of our methods over four state-of-the-art algorithms, especially when noisy data exist.

MULTIPLE TLS POINT CLOUD REGISTRATION BASED ON POINT PROJECTION IMAGES

Abstract. In this paper, an efficient and robust registration method of multiple point clouds is proposed. In our research, we assume that point clouds are acquired by Terrestrial Laser Scanning (TLS) systems, and the scanned environments have a relatively flat base plane such as the ground or a floor. Our method is based on an existing pairwise registration method based on point projection images, which can quickly register the point clouds under the above assumptions. In the method, sliced point clouds are projected onto the base plane, and a binary image with feature points is created. The registration is done by using feature points of the images based on the sample consensus strategy. In this paper, first, we improve the efficiency of the pairwise registration method by introducing height and occlusion information to the image. Then, a validity check method of pairwise registration using space-classified images is proposed to avoid exhaustive pairwise registration in the multiple point cloud registration process. Finally, an efficient multiple point cloud registration algorithm based on progressive creation of a point cloud connectivity graph using iterative rough and precise pairwise registration and the validity check method is proposed. The effectiveness of our method is shown through its application to three datasets of outdoor environments.

Markerless positional verification using template matching and triangulation of kV images acquired during irradiation for lung tumors treated in breath-hold

Lung tumors treated in breath-hold are subject to inter- and intra-breath-hold variations, which makes tumor position monitoring during each breath-hold important. A markerless technique is desirable, but limited tumor visibility on kV images makes this challenging. We evaluated if template matching + triangulation of kV projection images acquired during breath-hold stereotactic treatments could determine 3D tumor position. Band-pass filtering and/or digital tomosynthesis (DTS) were used as image pre-filtering/enhancement techniques. On-board kV images continuously acquired during volumetric modulated arc irradiation of (i) a 3D-printed anthropomorphic thorax phantom with three lung tumors (n = 6 stationary datasets, n = 2 gradually moving), and (ii) four patients (13 datasets) were analyzed. 2D reference templates (filtered DRRs) were created from planning CT data. Normalized cross-correlation was used for 2D matching between templates and pre-filtered/enhanced kV images. For 3D verification, each registration was triangulated with multiple previous registrations. Generally applicable image processing/algorithm settings for lung tumors in breath-hold were identified. For the stationary phantom, the interquartile range of the 3D position vector was on average 0.25 mm for 12° DTS + band-pass filtering (average detected positions in 2D = 99.7%, 3D = 96.1%, and 3D excluding first 12° due to triangulation angle = 99.9%) compared to 0.81 mm for band-pass filtering only (55.8/52.9/55.0%). For the moving phantom, RMS errors for the lateral/longitudinal/vertical direction after 12° DTS + band-pass filtering were 1.5/0.4/1.1 mm and 2.2/0.3/3.2 mm. For the clinical data, 2D position was determined for at least 93% of each dataset and 3D position excluding first 12° for at least 82% of each dataset using 12° DTS + band-pass filtering. Template matching + triangulation using DTS + band-pass filtered images could accurately determine the position of stationary lung tumors. However, triangulation was less accurate/reliable for targets with continuous, gradual displacement in the lateral and vertical directions. This technique is therefore currently most suited to detect/monitor offsets occurring between initial setup and the start of treatment, inter-breath-hold variations, and tumors with predominantly longitudinal motion.

"That Register is the Most Ancient and Useful of the Kingdom": Recording, Organizing, and Retrieving Information in the Fifteenth-Century Sicilian Chancery

This article argues that the late-medieval Catalan-Aragonese kings and their viceroys relied on record-keeping as a practical means of government, in essence for controlling the Kingdom of Sicily from a distance. More broadly, books, registers, and rolls are to be considered as crucial instruments through which late-medieval governments exercised their rule over complex political and social systems and were kept informed about their dominions' affairs. It is thus crucial to make those practical written tools into primary objects of research. By focusing on the "registers" of the royal chancery of the Kingdom of Sicily, this study examines the procedure for producing letters and privileges in connection to the establishment of a viceregal system; the strategies the Sicilian chancery staff adopted for recording documents, and the emergence of a method based on multiple registrations; the technical innovations they introduced for managing an increasing amount of information and facilitating its retrieval. Moreover, this study shows that the increasing attention of authorities towards record-keeping also generated a political conflict with Sicilian society, to the extent that the local parliament pursued the abolition of the registers of the royal chancery.

First Experience With Markerless Online 3D Spine Position Monitoring During SBRT Delivery Using a Conventional LINAC

The purpose was to report our initial experience with online markerless 3-dimensional (3D) spine position monitoring. We used template matching plus triangulation of fluoroscopic kilovoltage images acquired with the gantry-mounted imager during flattening filter-free volumetric modulated arc spine stereotactic body radiation therapy delivery on a conventional linear accelerator. Kilovoltage images were acquired at 7 frames per second and streamed to a stand-alone computer.Two-dimensional templates (1/°) containing the clinical target volume were generated from planning computed tomography (CT) data before the first fraction and matched to the (prefiltered) kilovoltage images during treatment.Each 2-dimensional registration was triangulated with multiple previous registrations, resulting in the 3D spine position offset from the planned position in realtime during treatment. If the offset was more than a certain threshold, the treatment was manually stopped and a cone beam CT scan was acquired to reposition the patient. During irradiation of 10 fractions in 3 patients, images were analyzed at an average rate of 1.0 to 1.3 frames per second; all other frames were excluded from the analysis because of limitations in processing speed. As a result of the start-up period of triangulation and poorer image quality at the start of treatment (lateral imaging angles), the first 3D position was determined after an average of 4.9seconds. On the basis of the position results, we interrupted the treatment beam 2 times for different patients. In all cases the spine position results corresponded well with the CT-cone beam CT match values used for subsequent repositioning. For the first time, we have determined the spine position during stereotactic body radiation therapy delivery on a standard linear accelerator using the gantry-mounted kilovoltage imager. This has the potential to increase confidence in the treatment, and the need for 2 treatment interruptions demonstrates the benefit of monitoring during irradiation. However, software improvements are needed to increase processing speed.

Provably Secure Multi-Server Authentication Protocol Using Fuzzy Commitment

Remote user authentication is a cryptographic mechanism through which a remote server verifies the legitimacy of an authorized user over an insecure communication channel. Most of the existing authentication schemes consider single-server environments and require multiple registrations of the same user for multiple servers. Moreover, most of these schemes do not consider biometric template revocation and error correction for noisy biometric signals. In addition, the existing schemes have several weaknesses, including stolen smart card attack, lack of user anonymity, user impersonation attack, and non-diversification of biometric data. To overcome these disadvantages, we propose a new three-factor authenticated key agreement scheme using a fuzzy commitment approach. The three factors used in the proposed scheme are the user’s password, smart card, and personal biometrics. The security of the proposed scheme is verified using a formal security analysis under the broadly accepted Real-Or-Random model for the session key security. The widely accepted Burrows-Abadi-Needham logic is also applied for mutual authentication between a legally registered user and a server, and formal security verification using the broadly accepted Automated Validation of Internet Security Protocols and Applications is performed for the proposed scheme through simulation to show that it is secure. In addition, the informal security analysis of the proposed scheme shows that the scheme can resist other known attacks. Finally, a comparative study of the proposed scheme with the existing related schemes is conducted to measure the tradeoff among the security and functionality features and the communication and computation costs.

The Impact of ICT in the Conduct of Elections in Nigeria

There is no gainsaying that technology has drastically reduced incidences of electoral malpractices such as: ballot stuffing, result sheet mutilation, manipulations, over voting, alteration of result sheets and hijacking of ballot boxes in the history of Nigeria elections. The Independent National Electoral Commission (INEC) has employed a number of innovative approaches to improve the management and conduct of elections in the country. As years pass by, INEC gets more sophisticated with its technologies in order to meet up with international standard. Therefore, this paper examines the impact of these technologies and the effect they have on election activities in Nigeria from 1999 general election to 2017. Results show that the introduction of these technologies: Electronic Voters Register(EVR), Automatic Fingerprints Identification System (AFIS) and Smart Card Reader (SCR) have reduced the incidence of multiple registration and multiple voting to the barest minimum while the development of e-collation support platform has drastically reduced incidence of result manipulation at collation centres. Hence, it is believed that the incorporation of Information and Communication Technology (ICT) in Nigeria electoral process has reduced excessive electoral fraud to the barest minimum and foster credible elections.

43. Intraoperative neurophysiological monitoring in spine surgery: A significant tool for neuronal protection and functional restoration

Although there is recent evidence for the role of intraoperative neurophysiological monitoring (IONM) in spine surgery, there are no uniform opinions on the optimal combination of the different tools. We analyzed the impact of the multimodal IONM (mIONM) on the preservation of neuronal structures and on functional restoration in a prospective series of our patients who underwent spine surgery. The mIONM approach in spine surgery involves the evaluation of somatosensory evoked potentials (SEPs) and motor evoked potentials (MEPs) with electrical transcranial stimulation, including the use of a multipulse technique with multiple myomeric registration of responses from limbs, and a single-pulse technique with D-wave registration through epi- and intradural recording, and free running and evoked electromyography. We observed an improvement of neurological status in 50% of the patients. The D-wave registration was the most useful intraoperative tool, especially when MEP and SEP responses were absent or poorly recordable. Our preliminary data confirm that mIONM plays a fundamental role in the identification and functional preservation of the spinal cord and nerve roots. It is highly sensitive and specific for detecting and avoiding neurological injury during spine surgery and represents a helpful tool for achieving optimal postoperative functional outcome.

Privacy Preserving Password-Based Multi-server Authenticated Key Agreement Protocol Using Smart Card

Clint–server based communication mechanism provides climbable environment for online services, where a user can obtain several services at any time and from anywhere via Internet. As Internet is an insecure communication medium, to achieve security and accountability in data transmission, authentication and key agreement protocols are being adopted. Majority of the existing protocols for mutual authentication are designed for single-server environment, which do not present scalable solution for multi-server environment as multiple registrations are required to perform by the user. Additionally, user must maintain multiple secret keys to access multiple application servers. On the contrary, multi-server authentication (MSA) mechanism presents a user-friendly solution to multiple-registration problem. Unfortunately, many MAS schemes consider trusted server environment, whereas some server may be semi-trusted. To address this issue, Kalra and Sood recently proposed MAS scheme, where all servers need not be entrusted. Kalra and Sood’s scheme is feasible for semi-trusted environment. By seeing its importance, we have thoroughly analyzed its security. Unfortunately, we have identified some security flaws in their scheme. Our aim is to overcome the flaws of Kalra and Sood’s scheme, and present privacy protected mutual authentication mechanism for multi-server communication. In this paper, we first pointed out the security failures of Kalra and Sood’s scheme and then proposed an improved MSA scheme to fix those vulnerabilities of existing MSA schemes. Our design is suitable for semi-trusted environment and protects anonymity. Moreover, the performance of the proposed protocol is comparable with the existing protocols.

Bayesian Registration of Functions With a Gaussian Process Prior

ABSTRACTWe present a Bayesian framework for registration of real-valued functional data. At the core of our approach is a series of transformations of the data and functional parameters, developed under a differential geometric framework. We aim to avoid discretization of functional objects for as long as possible, thus minimizing the potential pitfalls associated with high-dimensional Bayesian inference. Approximate draws from the posterior distribution are obtained using a novel Markov chain Monte Carlo (MCMC) algorithm, which is well suited for estimation of functions. We illustrate our approach via pairwise and multiple functional data registration, using both simulated and real datasets. Supplementary material for this article is available online.

A new method for registration of heterogeneous sensors in a dimensional measurement system

Registration of multiple sensors is a basic step in multi-sensor dimensional or coordinate measuring systems before any measurement. In most cases, a common standard is used to be measured by all sensors, and this may work well for general registration of multiple homogeneous sensors. However, when inhomogeneous sensors detect a common standard, it is usually very difficult to obtain the same information, because of the different working principles of the sensors. In this paper, a new method called multiple steps registration is proposed to register two sensors: a video camera sensor (VCS) and a tactile probe sensor (TPS). In this method, the two sensors measure two separated standards: a chrome circle on a reticle and a reference sphere with a constant distance between them, fixed on a steel plate. The VCS captures only the circle and the TPS touches only the sphere. Both simulations and real experiments demonstrate that the proposed method is robust and accurate in the registration of multiple inhomogeneous sensors in a dimensional measurement system.

High-precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization.

Atlases provide a framework for spatially mapping information from diverse sources into a common reference space. Specifically, brain atlases allow annotation of gene expression, cell morphology, connectivity, and activity. In larval zebrafish, advances in genetics, imaging, and computational methods now allow the collection of such information brain-wide. However, due to technical considerations, disparate datasets may use different references and may not be aligned to the same coordinate space. Two recent larval zebrafish atlases exemplify this problem: Z-Brain, containing gene expression, neural activity, and neuroanatomical segmentations, was acquired using immunohistochemical stains, while the Zebrafish Brain Browser (ZBB) was constructed from live scans of fluorescent reporters in transgenic larvae. Although different references were used, the atlases included several common transgenic patterns that provide potential “bridges” for transforming each into the other's coordinate space. We tested multiple bridging channels and registration algorithms and found that the symmetric diffeomorphic normalization algorithm improved live brain registration precision while better preserving cell morphology than B-spline-based registrations. Symmetric diffeomorphic normalization also corrected for tissue distortion introduced during fixation. Multi-reference channel optimization provided a transformation that enabled Z-Brain and ZBB to be co-aligned with precision of approximately a single cell diameter and minimal perturbation of cell and tissue morphology. Finally, we developed software to visualize brain regions in 3 dimensions, including a virtual reality neuroanatomy explorer. This study demonstrates the feasibility of integrating whole brain datasets, despite disparate reference templates and acquisition protocols, when sufficient information is present for bridging. Increased accuracy and interoperability of zebrafish digital brain atlases will facilitate neurobiological studies.

Non-rigid registration based model-free 3D facial expression recognition

We propose a novel feature extraction approach for 3D facial expression recognition by incorporating non-rigid registration in face-model-free analysis, which in turn makes feasible data-driven, i.e., feature-model-free recognition of expressions. The resulting simplicity of feature representation is due to the fact that facial information is adapted to the input faces via shape model-free dense registration, and this provides a dynamic feature extraction mechanism. This approach eliminates the necessity of complex feature representations as required in the case of static feature extraction methods, where the complexity arises from the necessity to model the local context; higher degree of complexity persists in deep feature hierarchies enabled by end-to-end learning on large-scale datasets. Face-model-free recognition implies independence from limitations and biases due to committed face models, bypassing complications of model fitting, and avoiding the burden of manual model construction. We show via information gain maps that non-rigid registration enables extraction of highly informative features, as it provides invariance to local-shifts due to physiognomy (subject invariance) and residual pose misalignments; in addition, it allows estimation of local correspondences of expressions. To maximize the recognition rate, we use the strategy of employing a rich but computationally manageable set of local correspondence structures, and to this effect we propose a framework to optimally select multiple registration references. Our features are re-sampled surface curvature values at individual coordinates which are chosen per expression-class and per reference pair. We show the superior performance of our novel dynamic feature extraction approach on three distinct recognition problems, namely, action unit detection, basic expression recognition, and emotion dimension recognition.

Automatic Thalamus Segmentation from Magnetic Resonance Images Using Multiple Atlases Level Set Framework (MALSF)

In this paper, we present an original multiple atlases level set framework (MALSF) for automatic, accurate and robust thalamus segmentation in magnetic resonance images (MRI). The contributions of the MALSF method are twofold. First, the main technical contribution is a novel label fusion strategy in the level set framework. Label fusion is achieved by seeking an optimal level set function that minimizes energy functional with three terms: label fusion term, image based term, and regularization term. This strategy integrates shape prior, image information and the regularity of the thalamus. Second, we use propagated labels from multiple registration methods with different parameters to take full advantage of the complementary information of different registration methods. Since different registration methods and different atlases can yield complementary information, multiple registration and multiple atlases can be incorporated into the level set framework to improve the segmentation performance. Experiments have shown that the MALSF method can improve the segmentation accuracy for the thalamus. Compared to ground truth segmentation, the mean Dice metrics of our method are 0.9239 and 0.9200 for left and right thalamus.

Inherent uncertainty involved in six-dimensional shift determination in ExacTrac imaging system

AbstractObjectiveThis study was conducted for the assessment of in-built systematic and random errors in the ExacTrac imaging system due to the software of Brainlab, on that basis; recommending a new quality control programme for ExacTrac imaging system.MethodsA program was developed to compare the image dataset of real time anthropomorphic pelvic phantom using ExacTrac with the reference image dataset from computed tomography. Images were acquired 20 times in a day, on single sitting for 20 conjugative days. On the basic of these translational and rotational shifts, systematic and random errors were calculated that had arisen due to multiple time image acquisition and image registration between acquired and reference image dataset of the phantom.ResultsRandom errors were found as 0·006 cm in right-left (Rt-Lt) direction, 0·008 cm in superior-inferior (Sup-Inf) direction and 0·012 cm in anterior-posterior (Ant-Post) direction. On this basic, margins were calculated using Van Herk formula; it was found that there were 0·02 cm inherent shift in Rt-Lt direction, 0·03 cm in Sup-Inf direction and 0·03 cm in Ant-Post direction.ConclusionThis study concluded that there was inherent error in ExacTrac system which can be quantified and used as a quality assurance tool for the ExacTrac system.

Performance Assessment for Brain MR Imaging Registration Methods.

Clinical brain MR imaging registration algorithms are often made available by commercial vendors without figures of merit. The purpose of this study was to suggest a rational performance comparison methodology for these products. Twenty patients were imaged on clinical 3T scanners by using 4 sequences: T2-weighted, FLAIR, susceptibility-weighted angiography, and T1 postcontrast. Fiducial landmark sites (n = 1175) were specified throughout these image volumes to define identical anatomic locations across sequences. Multiple registration algorithms were applied by using the T2 sequence as a fixed reference. Euclidean error was calculated before and after each registration and compared with a criterion standard landmark registration. The Euclidean effectiveness ratio is the fraction of Euclidean error remaining after registration, and the statistical effectiveness ratio is similar, but accounts for dispersion and noise. Before registration, error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 2.07 ± 0.55 mm, 2.63 ± 0.62 mm, and 3.65 ± 2.00 mm, respectively. Postregistration, the best error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 1.55 ± 0.46 mm, 1.34 ± 0.23 mm, and 1.06 ± 0.16 mm, with Euclidean effectiveness ratio values of 0.493, 0.181, and 0.096 and statistical effectiveness ratio values of 0.573, 0.352, and 0.929 for rigid mutual information, affine mutual information, and a commercial GE registration, respectively. We demonstrate a method for comparing the performance of registration algorithms and suggest the Euclidean error, Euclidean effectiveness ratio, and statistical effectiveness ratio as performance metrics for clinical registration algorithms. These figures of merit allow registration algorithms to be rationally compared.

Intraoperative Neurophysiological Monitoring in Spine Surgery: A Significant Tool for Neuronal Protection and Functional Restoration.

Although there is recent evidence for the role of intraoperative neurophysiological monitoring (IONM) in spine surgery, there are no uniform opinions on the optimal combination of the different tools. At our institution, multimodal IONM (mIONM) approach in spine surgery involves the evaluation of somatosensory evoked potentials (SEPs) and motor evoked potentials (MEPs) with electrical transcranial stimulation, including the use of a multipulse technique with multiple myomeric registration of responses from limbs, and a single-pulse technique with D-wave registration through epi- and intradural recording, and free running and evoked electromyography (frEMG and eEMG) with bilateral recording from segmental target muscles. We analyzed the impact of the mIONM on the preservation of neuronal structures and on functional restoration in a prospective series of patients who underwent spine surgery. We observed an improvement of neurological status in 50 % of the patients. The D-wave registration was the most useful intraoperative tool, especially when MEP and SEP responses were absent or poorly recordable. Our preliminary data confirm that mIONM plays a fundamental role in the identification and functional preservation of the spinal cord and nerve roots. It is highly sensitive and specific for detecting and avoiding neurological injury during spine surgery and represents a helpful tool for achieving optimal postoperative functional outcome.

Novel multihoming-based flow mobility scheme for proxy NEMO environment: A numerical approach to analyse handoff performance

With Network Mobility Basic Support Protocol (NEMO BSP), each communication should pass via the home agents of all mobile routers earlier reaching their destination at the time of frequent movement among the inter-technology handoff. This eventually results in performance deterioration of the real time application scenarios conducted on mobile nodes. Accordingly, applying the multihoming technique at any place, anywhere to provide uninterrupted internet connection in NEMO is becoming a significant area for current researchers. Although multiple care-of address registration between mobile routers along with its home agents can overcome some of the multihoming issues for NEMO, one still requires a dynamic flow redirection mechanism to support mobility management in NEMO. With the intention of reducing handoff delay, a novel multihoming-based flow mobility scheme on the PMIPv6 domain in NEMO (MF-PNEMO) is proposed in this paper. In addition, the performance of the MF-PNEMO scheme is evaluated through a numerical approach. The evaluation results confirms that the MF-PNEMO scheme outperforms the standard NEMO BSP as well as fast-proxy NEMO (FPNEMO) concerning handoff delay during inter-technology handoff.