Surface-based Registration Research Articles

Endoscopy-MR Image Fusion for Image Guided Procedures

Minimally invasive endoscope based abdominal procedures provide potential advantages over conventional open surgery such as reduced trauma, shorter hospital stay, and quick recovery. One major limitation of using this technique is the narrow view of the endoscope and the lack of proper 3D context of the surgical site. In this paper, we propose a rapid and accurate method to align intraoperative stereo endoscopic images of the surgical site with preoperative Magnetic Resonance (MR) images. Gridline light pattern is projected on the surgical site to facilitate the registration. The purpose of this surface-based registration is to provide 3D context of the surgical site to the endoscopic view. We have validated the proposed method on a liver phantom and achieved the surface registration error of 0.76 ± 0.11 mm.

Use of the surface-based registration function of computer-aided design/computer-aided manufacturing software in medical simulation software for three-dimensional simulation of orthognathic surgery

Three-dimensional (3D) computed tomography image models are helpful in reproducing the maxillofacial area; however, they do not necessarily provide an accurate representation of dental occlusion and the state of the teeth. Recent efforts have focused on improvement of dental imaging by replacement of computed tomography with other detailed digital images. Unfortunately, despite the advantages of medical simulation software in dentofacial analysis, diagnosis, and surgical simulation, it lacks adequate registration tools. Following up on our previous report on orthognathic simulation surgery using computer-aided design/computer-aided manufacturing (CAD/CAM) software, we recently used the registration functions of a CAD/CAM platform in conjunction with surgical simulation software. Therefore, we would like to introduce a new technique, which involves use of the registration functions of CAD/CAM software followed by transfer of the images into medical simulation software. This technique may be applicable when using various registration function tools from different software platforms.

Effectiveness of computer-assisted orthodontic treatment technology to achieve predicted outcomes

To evaluate the effectiveness of computer-assisted orthodontic treatment technology to produce the tooth position prescribed by the virtual treatment plan. Posttreatment models of 23 patients treated with SureSmile were digitally superimposed on their corresponding virtual treatment plan models utilizing best-fit surface-based registration. Individual tooth-position discrepancies between virtual treatment plan and actual outcome were computed. Discrepancies less than 0.5 mm in mesial-distal, facial-lingual, and vertical dimensions, and less than 2° for crown torque, tip, and rotation were considered clinically ideal. One-sided test of equivalence was performed on each discrepancy measurement, with P < .05 considered statistically significant. Mesial-distal tooth position was clinically ideal for all teeth with the exception of maxillary lateral incisors and second molars. Facial-lingual tooth position was clinically ideal for all teeth except maxillary central incisors, premolars, and molars, and mandibular incisors and second molars. Vertical tooth position was clinically ideal for all teeth except mandibular second molars. For crown torque, tip, and rotation, discrepancy exceeded the limits considered clinically ideal for all teeth except for crown torque on mandibular second premolars and crown tip on mandibular second premolars and first molars. The effectiveness of computer-assisted orthodontic treatment technology to achieve predicted tooth position varies with tooth type and dimension of movement.

Surface-based analyses of human, macaque, and chimpanzee cortical organization

Human and macaque cortex differ markedly in surface area (nine-fold), in their pattern of convolutions, and in the relationship of cortical areas to these convolutions. Nonetheless, there are numerous similarities and putative homologies in cortical organization revealed by architectonic and other anatomical methods and more recently by noninvasive functional imaging methods. There are also differences in functional organization, particularly in regions of rapid evolutionary expansion in the human lineage. This presentation will highlight recent progress in applying surface-based analysis and visualization methods that provide a powerful general approach for comparisons among primate species, including the macaque, chimpanzee, and human. One major facet involves surface-based atlases that are substrates for increasingly accurate cortical parcellations in each species as well as maps of functional organization revealed using resting-state and task-evoked fMRI. Additional insights into cortical parcellations as well as evolutionary relationships are provided by myelin maps that have been obtained noninvasively in each species. Together, these multiple modalities provide new insights regarding visual cortical organization in each species. Surface-based registration provides a key method for making objective interspecies comparisons, using explicit landmarks that represent known or candidate homologies between areas. Recent algorithmic improvements in landmark-based registration, coupled with refinements in the available set of candidate homologies, provide a fresh perspective on primate cortical evolution and species differences in the pattern of evolutionary expansion. Meeting abstract presented at VSS 2012

A study on the theoretical and practical accuracy of conoscopic holography-based surface measurements: toward image registration in minimally invasive surgery.

Registered medical images can assist with surgical navigation and enable image-guided therapy delivery. In soft tissues, surface-based registration is often used and can be facilitated by laser surface scanning. Tracked conoscopic holography (which provides distance measurements) has been recently proposed as a minimally invasive way to obtain surface scans. Moving this technique from concept to clinical use requires a rigorous accuracy evaluation, which is the purpose of our paper. We adapt recent non-homogeneous and anisotropic point-based registration results to provide a theoretical framework for predicting the accuracy of tracked distance measurement systems. Experiments are conducted a complex objects of defined geometry, an anthropomorphic kidney phantom and a human cadaver kidney. Experiments agree with model predictions, producing point RMS errors consistently < 1 mm, surface-based registration with mean closest point error < 1 mm in the phantom and a RMS target registration error of 0.8 mm in the human cadaver kidney. Tracked conoscopic holography is clinically viable; it enables minimally invasive surface scan accuracy comparable to current clinical methods that require open surgery.

Esthetic orthodontic treatment with a double J retractor and temporary anchorage devices

This clinical article reports an esthetic treatment option for managing a Class II malocclusion in an adult. The patient, a woman aged 24 years 2 months, had crowding and a convex profile. She was treated with maxillary first premolar extractions, a double J retractor, and temporary skeletal anchorage devices in the maxillary arch. Posttreatment records after 2 years showed excellent results with good occlusion and long-term stability.

An ICP variant with anisotropic weighting to accommodate measurement errors in A-Mode ultrasound-based registration

In computer-assisted surgery, navigation based on pre-operative images and intra-operative tracking requires fusion of data from different coordinate systems. Intra-operative registration is used to determine the spatial relationship between these coordinate systems. Feature-based registration methods rely on reference structures localized both in the pre-operative images and in the surgical site. Optically tracked A-Mode ultrasound (US) allows for non-invasive and cost-efficient digitization of bone surface points needed as input data for registration algorithms. It is especially attractive in combination with surface-based registration algorithms, such as the Iterative Closest Point algorithm and its variants, because they automatically localize the corresponding points, which are covered by soft tissue and, hence, not visible in the site. However, as transcutaneous palpation relies on some assumptions, e.g., regarding the average speed of sound of the scanned soft tissue, that are only partly justified in practice, errors occur that make transcutaneous palpation less reliable than direct palpation. Furthermore, optical tracking causes errors that have to be considered, especially if a so-called dynamic reference base is attached to the patient. The present work investigates how to reduce the effect of important error sources in A-Mode US-based registration. The major contributions are techniques for application-specific error modeling and new methods for surface-based registration with anisotropic weighting. This includes a Newton-like optimization scheme for point-to-point registration and a modified kd-tree-based algorithm for closest point computation. Various combinations of registration algorithms and modeling techniques are tested in a simulation study addressing periacetabular osteotomy, and it is clearly demonstrated that standard methods are not recommendable. On the contrary, the new algorithms allow for a substantial increase in registration accuracy and encourage further research in that field.

Individualized localization and cortical surface-based registration of intracranial electrodes

In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain-mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals-and coregistering functional results across subjects-remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individual's neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians.

Cortical Parcellations of the Macaque Monkey Analyzed on Surface-Based Atlases

Surface-based atlases provide a valuable way to analyze and visualize the functional organization of cerebral cortex. Surface-based registration (SBR) is a primary method for aligning individual hemispheres to a surface-based atlas. We used landmark-constrained SBR to register many published parcellation schemes to the macaque F99 surface-based atlas. This enables objective comparison of both similarities and differences across parcellations. Cortical areas in the macaque vary in surface area by more than 2 orders of magnitude. Based on a composite parcellation derived from 3 major sources, the total number of macaque neocortical and transitional cortical areas is estimated to be about 130-140 in each hemisphere.

Registration accuracy in the integration of laser-scanned dental images into maxillofacial cone-beam computed tomography images

A precision 3-dimensional (3D) head model can be fabricated by integrating a digital dental model into a maxillofacial 3D image. The integration requires accurate registration of 2 image modalities. The aims of this study were to determine the registration errors for implementation of laser-scanned dental images into cone-beam computed tomography (CBCT) scan data and to examine the influence of the registration area on the accuracy of registration. The CBCT scans were obtained from 30 adults, and the maxillofacial 3D images were reconstructed. Maxillary and mandibular dental casts were taken from the same subjects and scanned with a 3D laser scanner. The laser-scanned maxillary and mandibular dentition images were incorporated into the CBCT images of each arch in 3 ways according to the registration area: only the buccal surfaces, only the lingual surfaces, and both the buccal and lingual surfaces. Surface-based registration was performed by using an iterative closest point algorithm, and its errors were evaluated by measuring the 3D Euclidean distances between the surface points on the 2 images. The registration errors ranged from 0.27 to 0.33 mm. The mandibular arch did not show significant differences in registration errors according to the selected area for the registration. The maxillary arch, however, showed significant differences according to the registration area. When the lingual surfaces only were used for registration, the errors were greater than for the other 2 methods. The errors were least when both the buccal and lingual surfaces were used for registration. The results of this study indicate that accuracy in the integration of laser-scanned dental images into the maxillofacial CBCT images increases when a broad area is used for registration.

Brain surface conformal parameterization with the Ricci flow.

In brain mapping research, parameterized 3-D surface models are of great interest for statistical comparisons of anatomy, surface-based registration, and signal processing. Here, we introduce the theories of continuous and discrete surface Ricci flow, which can create Riemannian metrics on surfaces with arbitrary topologies with user-defined Gaussian curvatures. The resulting conformal parameterizations have no singularities and they are intrinsic and stable. First, we convert a cortical surface model into a multiple boundary surface by cutting along selected anatomical landmark curves. Secondly, we conformally parameterize each cortical surface to a parameter domain with a user-designed Gaussian curvature arrangement. In the parameter domain, a shape index based on conformal invariants is computed, and inter-subject cortical surface matching is performed by solving a constrained harmonic map. We illustrate various target curvature arrangements and demonstrate the stability of the method using longitudinal data. To map statistical differences in cortical morphometry, we studied brain asymmetry in 14 healthy control subjects. We used a manifold version of Hotelling's T(2) test, applied to the Jacobian matrices of the surface parameterizations. A permutation test, along with the cumulative distribution of p-values, were used to estimate the overall statistical significance of differences. The results show our algorithm's power to detect subtle group differences in cortical surfaces.

Automated landmark identification for human cortical surface-based registration

Volume-based registration (VBR) is the predominant method used in human neuroimaging to compensate for individual variability. However, surface-based registration (SBR) techniques have an inherent advantage over VBR because they respect the topology of the convoluted cortical sheet. There is evidence that existing SBR methods indeed confer a registration advantage over affine VBR. Landmark-SBR constrains registration using explicit landmarks to represent corresponding geographical locations on individual and atlas surfaces. The need for manual landmark identification has been an impediment to the widespread adoption of Landmark-SBR. To circumvent this obstacle, we have implemented and evaluated an automated landmark identification (ALI) algorithm for registration to the human PALS-B12 atlas. We compared ALI performance with that from two trained human raters and one expert anatomical rater (ENR). We employed both quantitative and qualitative quality assurance metrics, including a biologically meaningful analysis of hemispheric asymmetry. ALI performed well across all quality assurance tests, indicating that it yields robust and largely accurate results that require only modest manual correction (<10 min per subject). ALI largely circumvents human error and bias and enables high throughput analysis of large neuroimaging datasets for inter-subject registration to an atlas.

Mapping Human Cortical AreasIn VivoBased on Myelin Content as Revealed by T1- and T2-Weighted MRI

Noninvasively mapping the layout of cortical areas in humans is a continuing challenge for neuroscience. We present a new method of mapping cortical areas based on myelin content as revealed by T1-weighted (T1w) and T2-weighted (T2w) MRI. The method is generalizable across different 3T scanners and pulse sequences. We use the ratio of T1w/T2w image intensities to eliminate the MR-related image intensity bias and enhance the contrast to noise ratio for myelin. Data from each subject were mapped to the cortical surface and aligned across individuals using surface-based registration. The spatial gradient of the group average myelin map provides an observer-independent measure of sharp transitions in myelin content across the surface--i.e., putative cortical areal borders. We found excellent agreement between the gradients of the myelin maps and the gradients of published probabilistic cytoarchitectonically defined cortical areas that were registered to the same surface-based atlas. For other cortical regions, we used published anatomical and functional information to make putative identifications of dozens of cortical areas or candidate areas. In general, primary and early unimodal association cortices are heavily myelinated and higher, multimodal, association cortices are more lightly myelinated, but there are notable exceptions in the literature that are confirmed by our results. The overall pattern in the myelin maps also has important correlations with the developmental onset of subcortical white matter myelination, evolutionary cortical areal expansion in humans compared with macaques, postnatal cortical expansion in humans, and maps of neuronal density in non-human primates.

Automatic Correction of Registration Errors in Surgical Navigation Systems

Surgical navigation systems are used widely among all fields of modern medicine, including, but not limited to ENT- and maxillofacial surgery. As a fundamental prerequisite for image-guided surgery, intraoperative registration, which maps image to patient coordinates, has been subject to many studies and developments. While registration methods have evolved from invasive procedures like fixed stereotactic frames and implanted fiducial markers toward surface-based registration and noninvasive markers fixed to the patient's skin, even the most sophisticated registration techniques produce an imperfect result. Due to errors introduced during the registration process, the projection of navigated instruments into image data deviates up to several millimeter from the actual position, depending on the applied registration method and the distance between the instrument and the fiducial markers. We propose a method that allows to automatically and continually improve registration accuracy during intraoperative navigation after the actual registration process has been completed. The projections of navigated instruments into image data are inspected and validated by the navigation software. Errors in image-to-patient registration are identified by calculating intersections between the virtual instruments' axes and surfaces of hard bone tissue extracted from the patient's image data. The information gained from the identification of such registration errors is then used to improve registration accuracy by adding an additional pair of registration points at every location where an error has been detected. The proposed method was integrated into a surgical navigation system based on paired points registration with anatomical landmarks. Experiments were conducted, where registrations with deliberately misplaced point pairs were corrected with automatic error correction. Results showed an improvement in registration quality in all cases.

A multi-resolution scheme for distortion-minimizing mapping between human subcortical structures based on geodesic construction on Riemannian manifolds

In this paper, we deal with a subcortical surface registration problem. Subcortical structures including hippocampi and caudates have a small number of salient features such as heads and tails unlike cortical surfaces. Therefore, it is hard, if not impossible, to perform subcortical surface registration with only such features. It is also non-trivial for neuroanatomical experts to select landmarks consistently for subcortical surfaces of different subjects. We therefore present a landmark-free approach for subcortical surface registration by measuring the amount of mesh distortion between subcortical surfaces assuming that the surfaces are represented by meshes. The input meshes can be constructed using any surface modeling tool available in the public domain since our registration method is independent of a surface modeling process. Given the source and target surfaces together with their representing meshes, the vertex positions of the source mesh are iteratively displaced while preserving the underlying surface shape in order to minimize the distortion to the target mesh. By representing each surface mesh as a point on a high-dimensional Riemannian manifold, we define a distance metric on the manifold that measures the amount of distortion from a given source mesh to the target mesh, based on the notion of isometry while penalizing triangle flipping. Under this metric, we reduce the distortion minimization problem to the problem of constructing a geodesic curve from the moving source point to the fixed target point on the manifold while satisfying the shape-preserving constraint. We adopt a multi-resolution framework to solve the problem for distortion-minimizing mapping between the source and target meshes. We validate our registration scheme through several experiments: distance metric comparison, visual validation using real data, robustness test to mesh variations, feature alignment using anatomic landmarks, consistency with previous clinical findings, and comparison with a surface-based registration method, LDDMM-surface.

Evaluation of intersession 3D‐TRUS to 3D‐TRUS image registration for repeat prostate biopsies

3D-TRUS-guided prostate biopsy permits a 3D record of biopsy cores, supporting the planning of targets to resample or avoid during repeat biopsy sessions. Image registration is required in order to map biopsy targets planned on a previous session's 3D-TRUS image into the context of the current session. The authors evaluated the performance of surface- and intensity-based rigid and nonrigid registration algorithms for this task using a clinically motivated success criterion of a maximum 2.5 mm target registration error (TRE). The authors collected two 3D-TRUS images for each of 13 patients, where each image was collected in a separate biopsy session, and the sessions were 1 week apart. The authors tested the iterative closest point and thin-plate spline surface-based registration methods, and the block matching and B-spline intensity-based methods. Manually marked intrinsic fiducials (calcifications) were used to calculate a TRE for each of the tested methods. In addition, error ellipsoids, anisotropy, and variability due to image segmentation were analyzed. All analysis was performed separately for the peripheral zone since this area harbors up to 80% of all prostate cancer. Only the intensity-based nonrigid registration method met the success criterion for both the whole gland and the peripheral zone. Segmentation was a substantial contributor to registration error variability for the surface-based methods, and the surface-based methods resulted in greater error volumes and anisotropy. Intensity-based rigid registration is clinically sufficient to register regions outside the peripheral zone, but nonrigid registration is required in order to register the peripheral zone with clinically needed accuracy. The clinical advantage of using nonrigid registration is questionable since the difference between the RMS TREs for rigid and nonrigid intensity-based registration could be considered to be small (0.3 mm) and is statistically significant. If the added clinical value in performing a nonrigid registration is insufficient given the additional time required for this computation, rigid registration alone may be suitable.

Intraprocedural Registration for Image-Guided Kidney Surgery

This paper reviews the process of using surface-based registration techniques for image-guided kidney surgery and presents data for both open and minimally invasive kidney surgery either by robot or by hand.

Registration of 3-Dimensional Facial Photographs for Clinical Use

To objectively evaluate treatment outcomes in oral and maxillofacial surgery, pre- and post-treatment 3-dimensional (3D) photographs of the patient's face can be registered. For clinical use, it is of great importance that this registration process is accurate (< 1 mm). The purpose of this study was to determine the accuracy of different registration procedures. Fifteen volunteers (7 males, 8 females; mean age, 23.6 years; range, 21 to 26 years) were invited to participate in this study. Three-dimensional photographs were captured at 3 different times: baseline (T(0)), after 1 minute (T(1)), and 3 weeks later (T(2)). Furthermore, a 3D photograph of the volunteer laughing (T(L)) was acquired to investigate the effect of facial expression. Two different registration methods were used to register the photographs acquired at all different times: surface-based registration and reference-based registration. Within the surface-based registration, 2 different software packages (Maxilim [Medicim NV, Mechelen, Belgium] and 3dMD Patient [3dMD LLC, Atlanta, GA]) were used to register the 3D photographs acquired at the various times. The surface-based registration process was repeated with the preprocessed photographs. Reference-based registration (Maxilim) was performed twice by 2 observers investigating the inter- and intraobserver error. The mean registration errors are small for the 3D photographs at rest (0.39 mm for T(0)-T(1) and 0.52 mm for T(0)-T(2)). The mean registration error increased to 1.2 mm for the registration between the 3D photographs acquired at T(0) and T(L). The mean registration error for the reference-based method was 1.0 mm for T(0)-T(1), 1.1 mm for T(0)-T(2), and 1.5 mm for T(0) and T(L). The mean registration errors for the preprocessed photographs were even smaller (0.30 mm for T(0)-T(1), 0.42 mm for T(0)-T(2), and 1.2 mm for T(0) and T(L)). Furthermore, a strong correlation between the results of both software packages used for surface-based registration was found. The intra- and interobserver error for the reference-based registration method was found to be 1.2 and 1.0 mm, respectively. Surface-based registration is an accurate method to compare 3D photographs of the same individual at different times. When performing the registration procedure with the preprocessed photographs, the registration error decreases. No significant difference could be found between both software packages that were used to perform surface-based registration.

Scaled, patient-specific 3D vertebral model reconstruction based on 2D lateral fluoroscopy

Accurate three-dimensional (3D) models of lumbar vertebrae are required for image-based 3D kinematics analysis. MRI or CT datasets are frequently used to derive 3D models but have the disadvantages that they are expensive, time-consuming or involving ionizing radiation (e.g., CT acquisition). An alternative method using 2D lateral fluoroscopy was developed. A technique was developed to reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image and a statistical shape model of the lumbar vertebrae. Four cadaveric lumbar spine segments and two statistical shape models were used for testing. Reconstruction accuracy was determined by comparison of the surface models reconstructed from the single lateral fluoroscopic images to the ground truth data from 3D CT segmentation. For each case, two different surface-based registration techniques were used to recover the unknown scale factor, and the rigid transformation between the reconstructed surface model and the ground truth model before the differences between the two discrete surface models were computed. Successful reconstruction of scaled surface models was achieved for all test lumbar vertebrae based on single lateral fluoroscopic images. The mean reconstruction error was between 0.7 and 1.6 mm. A scaled, patient-specific surface model of the lumbar vertebra from a single lateral fluoroscopic image can be synthesized using the present approach. This new method for patient-specific 3D modeling has potential applications in spine kinematics analysis, surgical planning, and navigation.

Using Superimposition of 3-Dimensional Cone-Beam Computed Tomography Images with Surface-Based Registration in Growing Patients

The purpose of this research was to evaluate a new method of superimposing detailed cone-beam computed tomography (CBCT) images. This study used 5 different software programs to transform the digital imaging and communication in medicine (DICOM) data from CBCT image into polygon data. The data conversion errors from different software programs were verified by the poly-acetal ball test and the dry skull test. The iterative closest point (ICP) method was used for precise superimposition. To evaluate changes related to growth, three different domains were superimposed in order to investigate appropriate areas for evaluation by the ICP method. The ICP method in the cranial base (excluding the peripheral zone) was indicated as the most reliable surface in this research. There were no measurement errors in converting the image data between software programs. The ICP method in the cranial base (excluding the peripheral zone) is one of the most accurate methods for superimposition when the mandibular rotation or displacement has not occurred during growth or treatment. This 3-dimensional (3D) superimposition technique can be used for a valid and reproducible assessment of treatment outcomes for growing subjects. This method is considered to be of clinical value because of the manageability and 3D accuracy of the data comparison with multi planar reconstruction (MPR) images.