Reconstruction Of Surface Models Research Articles

Validation of statistical shape model based reconstruction of the proximal femur—A morphology study

Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.

Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph

The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching. Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction. The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models. The technique could reconstruct the surface models of all 14 pelvises directly from the landmark-based initialization. Depending on the surface-based matching techniques, the reconstruction errors were slightly different. When a surface-based iterative affine registration was used, an average reconstruction error of 1.6 mm was observed. This error was increased to 1.9 mm, when a surface-based iterative scaled rigid registration was used. It is feasible to reconstruct a scaled, patient-specific surface model of the pelvis from single standard AP x-ray radiograph using the present approach. The unknown scale of the reconstructed model can be estimated by performing a surface-based 3D/3D matching.

A real-time FPGA architecture for 3D reconstruction from integral images

In this paper, we present a hardware architecture for real-time three-dimensional (3D) surface model reconstruction from Integral Images (InIms). The proposed parallel digital system realizes a number of computational-heavy calculations in order to achieve real-time operation. The processing elements are deployed in a systolic architecture and operate on multiple image areas simultaneously. Moreover, memory organization allows random access to image data and copes with the increased processing throughput of the system. Operating results reveal that the proposed architecture is able to process 3D data at a real-time rate. The proposed system can handle large sized InIms in real time and outputs 3D scenes of enhanced depth and detailed texture, which apply to emerging 3D applications.

Surface Reconstruction Using Dexel Data From Three Sets of Orthogonal Rays

Triple-dexel modeling is a geometric representation method, which depicts the intersection of a solid with rays cast in three orthogonal directions. Due to its fast Boolean operations, simple data structure, and easy implementation, triple-dexel modeling is highly suitable for real-time graphics-based simulation applications such as numerical control (NC) machining verification and virtual sculpting. This paper presents a novel surface reconstruction method from triple-dexel data by first converting the triple-dexel data into contours on three sets of orthogonal slices and then generating the solid’s boundary surface in triangular facets from these contours. The developed method is faster than the voxel-based method, and the reconstructed surface model is more accurate than the surface reconstructed from voxel representation using the marching cube algorithm. Examples are given to demonstrate the ability of surface reconstruction from the triple-dexel model in virtual sculpting.

A system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images.

This paper presents a system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images. Our system requires two X-ray images of a patient with one acquired from the anterior-posterior direction and the other from the axial direction. A custom-designed cage is utilized in our system to calibrate both images. Starting from bone contours that are interactively identified from the X-ray images, our system constructs a patient-specific surface model of the proximal femur based on a statistical model based 2D/3D reconstruction algorithm. In this paper, we present the design and validation of the system with 25 bones. An average reconstruction error of 0.95 mm was observed.

Novel Free-form Surface 3D Laser Scanning System

An original design program of three-dimensional laser scanning system is introduced in terms of mechanical structure, control system and operating system structure. The presented system integrates optical, mechanical, electronic technologies, it includes advanced data processing technology, laser scanning technology, advanced control technology, robot technology and so on, so that 3D surface inspection and surface digital reconstruction are implemented automatically. The system consists of a laser probe with electric drive, a C-typeslide arm, lifting turntables, electronic control system and a master computer. The object with freeform surface can be scanned without any blind point. Furthermore, the adaptive path planning is available for the measurement process. The effectiveness of the proposed measurement machine is verified. Experimental result demonstrates that the scanning precision of the system is 0.1 mm and the scanning speed is 10 000 pts/s. The system can be applied in the surface data inspection and model reconstruction for small-sized workpiece and mould.

A 2D/3D correspondence building method for reconstruction of a patient-specific 3D bone surface model using point distribution models and calibrated X-ray images

Constructing a 3D bone surface model from a limited number of calibrated 2D X-ray images (e.g. 2) and a 3D point distribution model is a challenging task, especially, when we would like to construct a patient-specific surface model of a bone with pathology. One of the key steps for such a 2D/3D reconstruction is to establish correspondences between the 2D images and the 3D model. This paper presents a 2D/3D correspondence building method based on a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformations to find a fraction of best matched 2D point pairs between features extracted from the X-ray images and those extracted from the 3D model. The estimated point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one, whose solutions are well studied. Incorporating this 2D/3D correspondence building method, a 2D/3D reconstruction scheme combining a statistical instantiation with a regularized shape deformation has been developed. Comprehensive experiments on clinical datasets and on images of cadaveric femurs with both non-pathologic and pathologic cases are designed and conducted to evaluate the performance of the 2D/3D correspondence building method as well as that of the 2D/3D reconstruction scheme. Quantitative and qualitative evaluation results are given, which demonstrate the validity of the present method and scheme.

Unwrap mosaics

We introduce a new representation for video which facilitates a number of common editing tasks. The representation has some of the power of a full reconstruction of 3D surface models from video, but is designed to be easy to recover from a priori unseen and uncalibrated footage. By modelling the image-formation process as a 2D-to-2D transformation from an object's texture map to the image, modulated by an object-space occlusion mask, we can recover a representation which we term the "unwrap mosaic". Many editing operations can be performed on the unwrap mosaic, and then re-composited into the original sequence, for example resizing objects, repainting textures, copying/cutting/pasting objects, and attaching effects layers to deforming objects.

Accurate and Robust Reconstruction of a Surface Model of the Proximal Femur From Sparse-Point Data and a Dense-Point Distribution Model for Surgical Navigation

Constructing a 3-D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1) leave-one-out experiment, 2) experiment on evaluating the present approach for handling pathology, 3) experiment on evaluating the present approach for handling outliers, and 4) experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

A Novel Design of in Pipe Robot for Inner Surface Inspection of Large Size Pipes#

This paper presents a novel design of robot measuring machine for inner surface inspection of large size pipes. This prototype represents an integrated mechatronic structure design of a high precision measurement machine. In mechanical design the presented measurement equipment consists of two main parts, an automatic in-pipe mobile vehicle with four degree of freedom and a 3D laser scanning system. In electronic design, the system is embedded with a professional software package, which includes a number of function modules such as data processing and analysis, surface model reconstruction, and finite element analysis etc. Further the intelligence of the machine is enhanced with an adaptive control strategy to suppress vibration disturbance, caused by environmental noise, so that the measurement accuracy of the robot system is guaranteed within the specified precision level (micrometer). The measurement diameter can range from 580 to 1000 mm. Several bench tests are presented to demonstrate the measuring machine performance.

Virtual Temporal Bone Anatomy

The Visible Human Project (VHP) initiated by the U.S. National Library of Medicine has drawn much attention and interests from around the world. The Visible Chinese Human (VCH) project has started in China. The current study aims at acquiring a feasible virtual methodology for reconstructing the temporal bone of the Chinese population, which may provide an accurate 3-D model of important temporal bone structures that can be used in teaching and patient care for medical scientists and clinicians. A series of sectional images of the temporal bone were generated from section slices of a female cadaver head. On each sectional image, SOIs(structures of interest) were segmented by carefully defining their contours and filling their areas with certain gray scale values. The processed volume data were then inducted into the 3D Slicer software (developed by the Surgical Planning Lab at Brigham and Women's Hospital and the MIT AI Lab) for resegmentation and generation of a set of tagged images of the SOIs. 3D surface models of SOIs were then reconstructed from these images. The temporal bone and structures in the temporal bone, including the tympanic cavity, mastoid cells, sigmoid sinus and internal carotid artery, were successfully reconstructed. The orientation of and spatial relationship among these structures were easily visualized in the reconstructed surface models. The 3D Slicer software can be used for 3-dimensional visualization of anatomic structures in the temporal bone, which will greatly facilitate the advance of knowledge and techniques critical for studying and treating disorders involving the temporal bone.

In Vivo Elongation of the Palmar and Dorsal Scapholunate Interosseous Ligament

To investigate the elongation of the palmar and dorsal subregions of the scapholunate interosseous ligament (SLIL) in healthy human subjects throughout a complete range of wrist motion. The 3-dimensional in vivo kinematics of the scaphoid and lunate were determined in both wrists of 13 female and 13 male volunteers from computed tomography volume images. For each wrist the palmar and dorsal insertions of the SLIL were identified on reconstructed surface models of the scaphoid and lunate. The interbone distances between the palmar and dorsal sites were calculated for the neutral wrist position. Elongations were then calculated after applying the 3-dimensional kinematics to the scaphoid and lunate. A multiple linear regression model was used to determine if elongations varied significantly as a function of wrist flexion/extension and radioulnar deviation. From pure wrist extension to pure wrist flexion, the fibers of the SLIL at the palmar insertion site increased significantly, from 29% shortening to 27% elongation, and the dorsal insertion decreased from 26% to 4% shortening with respect to the fiber lengths in the neutral position. From pure radial deviation to pure ulnar deviation, the elongation of the palmar insertion significantly decreased from 9% elongation to 21% shortening. There was no notable change in dorsal elongation with wrist radioulnar deviation. The multiple linear regression model predicted that there would be minimal elongation of the palmar and dorsal fibers at the wrist position along the dart thrower's path from radial extension to ulnar flexion. In vivo elongation of the palmar and dorsal fibers of the SLIL varied with wrist position. The palmar fibers lengthened and the dorsal fibers shortened with wrist flexion and the opposite occurred with wrist extension. Scapholunate interosseous ligament elongation was minimal as the wrist was positioned along the dart thrower's path.

A novel quantitative cross-validation of different cortical surface reconstruction algorithms using MRI phantom

Cortical surface reconstruction is important for functional brain mapping and morphometric analysis of the brain cortex. Several methods have been developed for the faithful reconstruction of surface models which represent the true cortical surface in both geometry and topology. However, there has been no explicit comparison study among those methods because each method has its own procedures, file formats, coordinate systems, and use of the reconstructed surface. There has also been no explicit evaluation method except visual inspection to validate the whole-cortical surface models quantitatively. In this study, we presented a novel phantom-based validation method of the cortical surface reconstruction algorithm and quantitatively cross-validated the three most prominent cortical surface reconstruction algorithms which are used in Freesurfer, BrainVISA, and CLASP, respectively. The validation included geometrical accuracy and mesh characteristics such as Euler number, fractal dimension (FD), total surface area, and local density of points. CLASP showed the best geometric/topologic accuracy and mesh characteristics such as FD and total surface area compared to Freesurfer and BrainVISA. In the validation of local density of points, Freesurfer and BrainVISA showed more even distribution of points on the cortical surface compared to CLASP.

Structure Investigation of Ag(111)(√7×√7)R19°-SCH3 by X-ray Standing Waves: A Case of Thiol-Induced Substrate Reconstruction

The structure of the Ag(111)(radical7x radical7)R19 degrees-CH3S surface phase, formed by interaction of Ag(111) with gas-phase dimethyl disulfide, (CH3S)2, has been investigated by normal-incidence X-ray standing wave (NIXSW) analysis, using (111), (11), and (200) Bragg reflections. The resulting NIXSW structural parameter values clearly exclude any simple overlayer adsorption model on an Ag unreconstructed surface. A reconstructed surface model is proposed that is consistent with the NIXSW measurements and with previous scanning tunneling microscopy results. This comprises a near-hexagonal Ag surface layer with an Ag density of only 3/7 that of the underlying substrate layers; the methanethiolate molecules are adsorbed into 3-fold coordinated hollow sites on this open layer. The results are discussed in the context of the very limited published studies of longer alkyl chain thiolates on Ag(111).

A Bayesian method for probable surface reconstruction and decimation

We present a Bayesian technique for the reconstruction and subsequent decimation of 3D surface models from noisy sensor data. The method uses oriented probabilistic models of the measurement noise and combines them with feature-enhancing prior probabilities over 3D surfaces. When applied to surface reconstruction, the method simultaneously smooths noisy regions while enhancing features such as corners. When applied to surface decimation, it finds models that closely approximate the original mesh when rendered. The method is applied in the context of computer animation where it finds decimations that minimize the visual error even under nonrigid deformations.

Scene modelling from sparse 3D data

Sparse 3D measurements of real scenes are readily estimated from N-view image sequences using structure-from-motion techniques. In this paper, we present a geometric theory for reconstruction of surface models from sparse 3D data captured from N camera views. Based on this theory, we introduce a general N-view algorithm for reconstruction of 3D models of arbitrary scenes from sparse data. This algorithm reconstructs a surface model which converges to an approximation of the real scene surfaces and is consistent with the feature visibility in all N-views. To achieve efficient reconstruction independent of the number of views a recursive reconstruction algorithm is developed which integrates the feature visibility independently for each view. This approach is shown to converge to an approximation of the real scene structure and have a computational cost which is linear in the number of views. It is assumed that structure-from-motion estimates of 3D feature locations are consistent with the multiple view visual geometry and do not contain outliers. Uncertainty in 3D feature estimates is incorporated in the feature visibility to achieve reliable reconstruction in the presence of noise inherent in estimates of 3D scene structure from real image sequences. Results are presented for reconstruction of both real and synthetic scenes together with an evaluation of the reconstruction performance in the presence of noise. The algorithm presented in this paper provides a reliable and computationally efficient approach to model reconstruction from sparse 3D scene data.

Scanning Tunneling Microscopy Investigation of the Structure of Methanethiolate on Ag(111)

Scanning tunneling microscopy (STM) has been used to investigate the structure of the ordered methanethiolate overlayer formed on Ag(111) by reaction at room temperature with dimethyl disulfide. High-resolution images show an ordered structure with three inequivalent atomic-scale protrusions within each ( radical7 x radical7)R19 degrees surface unit mesh which can be reconciled with methanethiolate species on a regular lateral submesh, similar to that proposed in the multilayer ( radical7 x radical7)R19 degrees -S sulfide phase previously reported. STM imaging during dynamic dosing also provides evidence for a significant change in the outermost layer Ag atom density, consistent with a reconstructed surface model. Possible models for this reconstruction are presented and discussed in the light of available information.

Manufacturable surface reconstruction from complex contours

To retrieve the geometric information contained in CT images, a surface reconstruction method, which is based on the similarity between the corresponding contours of adjacent sections, is presented in this paper. The correspondence of the contours of adjacent sections is determined by incorporating the topological rules and overlaps of the convex hulls of the contours. Then, the similar vertices of the corresponding contours are matched using a two‐phase strategy, consisting of overall matching followed by local matching. Dissimilar portions are extracted to construct the triangulable spatial dissimilar polygons. Finally, triangular meshes interpolating the contours are obtained by triangulating the dissimilar polygons and similar portions separately. The reconstructed surface models can be used in rapid prototyping as well as visualization. Experimental results demonstrate the validity of the method in reconstructing the surface from severe dissimilar contours.

Geometric fusion for a hand-held 3D sensor

Abstract. This article presents a geometric fusion algorithm developed for the reconstruction of 3D surface models from hand-held sensor data. Hand-held systems allow full 3D movement of the sensor to capture the shape of complex objects. Techniques previously developed for reconstruction from conventional 2.5D range image data cannot be applied to hand-held sensor data. A geometric fusion algorithm is introduced to integrate the measured 3D points from a hand-held sensor into a single continuous surface. The new geometric fusion algorithm is based on the normal-volume representation of a triangle, which enables incremental transformation of an arbitrary mesh into an implicit volumetric field function. This system is demonstrated for reconstruction of surface models from both hand-held sensor data and conventional 2.5D range images.

Abstract: Automatic Reconstruction of 3D Multi-Valued Surface Models from Interpreted Seisimic Data

Abstract: Automatic Reconstruction of 3D Multi-Valued Surface Models from Interpreted Seisimic Data