Wuyang Shui

A novel skull registration based on global and local deformations for craniofacial reconstruction

Craniofacial reconstruction is important in forensic identification. It aims to estimate a facial appearance for human skeletal remains using the relationship between the soft tissue and the underlying bone structure. Various computerized methods have been developed in recent decades. An effective way is to deform a reference skull to the discovered skull, and then apply the same deformation to the skin associated with the reference skull to provide an approximate face for the discovered skull. For this method, the better the two skulls match each other, the more face-like the reconstructed skin surface will be. In this paper, we present a novel skull registration method that can match the two skulls closely, so as to improve the accuracy of the reconstruction. It combines both global and local deformations. A generic thin-plate spline (TPS)-based deformation, which is global, is applied first to roughly align the two skulls based on two groups of manually defined landmarks. Afterwards, the two skulls are largely matched, except some regions, on which some new landmarks are automatically marked. A compact support radial basis functions (CSRBF)-based deformation, which is local, will then be performed on these regions to adjust the initial alignment of the two skulls. Such adjustment can be repeatedly implemented until the two skulls have optimal alignment. In addition, all the skulls and face involved in the registration are represented by their single outer surfaces to facilitate the reconstruction procedure. The experiments demonstrate that our method can create a plausible face even when the reference skull is very different from the discovered skull. As a result, we can make full use of our database to provide multiple estimates for a principle components analysis (PCA) for the final reconstruction.

The production of digital and printed resources from multiple modalities using visualization and three-dimensional printing techniques.

PurposeVirtual digital resources and printed models have become indispensable tools for medical training and surgical planning. Nevertheless, printed models of soft tissue organs are still challenging to reproduce. This study adopts open source packages and a low-cost desktop 3D printer to convert multiple modalities of medical images to digital resources (volume rendering images and digital models) and lifelike printed models, which are useful to enhance our understanding of the geometric structure and complex spatial nature of anatomical organs.Materials and methodsNeuroimaging technologies such as CT, CTA, MRI, and TOF-MRA collect serial medical images. The procedures for producing digital resources can be divided into volume rendering and medical image reconstruction. To verify the accuracy of reconstruction, this study presents qualitative and quantitative assessments. Subsequently, digital models are archived as stereolithography format files and imported to the bundled software of the 3D printer. The printed models are produced using polylactide filament materials.ResultsWe have successfully converted multiple modalities of medical images to digital resources and printed models for both hard organs (cranial base and tooth) and soft tissue organs (brain, blood vessels of the brain, the heart chambers and vessel lumen, and pituitary tumor). Multiple digital resources and printed models were provided to illustrate the anatomical relationship between organs and complicated surrounding structures. Three-dimensional printing (3DP) is a powerful tool to produce lifelike and tangible models.ConclusionsWe present an available and cost-effective method for producing both digital resources and printed models. The choice of modality in medical images and the processing approach is important when reproducing soft tissue organs models. The accuracy of the printed model is determined by the quality of organ models and 3DP. With the ongoing improvement of printing techniques and the variety of materials available, 3DP will become an indispensable tool in medical training and surgical planning.

A regional method for craniofacial reconstruction based on coordinate adjustments and a new fusion strategy

Craniofacial reconstruction recreates a facial outlook from the cranium based on the relationship between the face and the skull to assist identification. But craniofacial structures are very complex, and this relationship is not the same in different craniofacial regions. Several regional methods have recently been proposed, these methods segmented the face and skull into regions, and the relationship of each region is then learned independently, after that, facial regions for a given skull are estimated and finally glued together to generate a face. Most of these regional methods use vertex coordinates to represent the regions, and they define a uniform coordinate system for all of the regions. Consequently, the inconsistence in the positions of regions between different individuals is not eliminated before learning the relationships between the face and skull regions, and this reduces the accuracy of the craniofacial reconstruction. In order to solve this problem, an improved regional method is proposed in this paper involving two types of coordinate adjustments. One is the global coordinate adjustment performed on the skulls and faces with the purpose to eliminate the inconsistence of position and pose of the heads; the other is the local coordinate adjustment performed on the skull and face regions with the purpose to eliminate the inconsistence of position of these regions. After these two coordinate adjustments, partial least squares regression (PLSR) is used to estimate the relationship between the face region and the skull region. In order to obtain a more accurate reconstruction, a new fusion strategy is also proposed in the paper to maintain the reconstructed feature regions when gluing the facial regions together. This is based on the observation that the feature regions usually have less reconstruction errors compared to rest of the face. The results demonstrate that the coordinate adjustments and the new fusion strategy can significantly improve the craniofacial reconstructions.

Robust surface segmentation and edge feature lines extraction from fractured fragments of relics

Abstract Surface segmentation and edge feature lines extraction from fractured fragments of relics are essential steps for computer assisted restoration of fragmented relics. As these fragments were heavily eroded, it is a challenging work to segment surface and extract edge feature lines. This paper presents a novel method to segment surface and extract edge feature lines from triangular meshes of irregular fractured fragments. Firstly, a rough surface segmentation is accomplished by using a clustering algorithm based on the vertex normal vector. Secondly, in order to differentiate between original and fracture faces, a novel integral invariant is introduced to compute the surface roughness. Thirdly, an accurate surface segmentation is implemented by merging faces based on face normal vector and roughness. Finally, edge feature lines are extracted based on the surface segmentation. Some experiments are made and analyzed, and the results show that our method can achieve surface segmentation and edge extraction effectively.

3D craniofacial reconstruction using reference skull-face database

Craniofacial reconstruction is aiming at estimating the outlook of an unknown or an unidentified skull. In this paper, we present an approach of the craniofacial reconstruction of Chinese people. Firstly, we build a skull-face database and classify it in terms of age, area and gender. Then Thin-Plate spline (TPS) is adopted to achieve non-rigid registration between the unidentified skull and reference skull. however, the craniofacial result is determined by the choice of reference template. Here a statistic method is adopted to estimate outlook from subclass of skull-face database using Principle component analysis. In order to improve the accuracy of the result, we select the suitable organ (eyes, nose and mouth) for the statistic result based on anatomy principle from the database and achieve the organ and face integration to build the final outlook. Finally, we show some experiments of the algorithm.

Automatic planar shape segmentation from indoor point clouds

The use of a terrestrial laser scanner (TLS) has become a popular technique for the acquisition of 3D scenes in architecture and design. Surface reconstruction is used to generate a digital model from the acquired point clouds. However, the model often consists of excessive data, limiting real-time user experiences that make use of the model. In this study, we present a coarse to fine planar shape segmentation method for indoor point clouds, which results in the digital model of an indoor scene being represented by a small number of planar patches. First, the Gaussian map and region growing techniques are used to coarsely segment the planar shape from sampled point clouds. Then, the best-fit-plane is calculated by random sample consensus (RANSAC), avoiding the negative impact of outliers. Finally, the refinement of planar shape is produced by projecting point clouds onto the corresponding bestfit-plane. Our method has been demonstrated to be robust towards noise and outliers in the scanned point clouds and overcomes the limitations of over- and under-segmentation. We have tested our system and algorithms on real datasets and experiments show the reliability of the proposed method against existing region-growing methods.

Densely calculated facial soft tissue thickness for craniofacial reconstruction in Chinese adults

Craniofacial reconstruction (CFR) is used to recreate a likeness of original facial appearance for an unidentified skull; this technique has been applied in both forensics and archeology. Many CFR techniques rely on the average facial soft tissue thickness (FSTT) of anatomical landmarks, related to ethnicity, age, sex, body mass index (BMI), etc. Previous studies typically employed FSTT at sparsely distributed anatomical landmarks, where different landmark definitions may affect the contrasting results. In the present study, a total of 90,198 one-to-one correspondence skull vertices are established on 171 head CT-scans and the FSTT of each corresponding vertex is calculated (hereafter referred to as densely calculated FSTT) for statistical analysis and CFR. Basic descriptive statistics (i.e., mean and standard deviation) for densely calculated FSTT are reported separately according to sex and age. Results show that 76.12% of overall vertices indicate that the FSTT is greater in males than females, with the exception of vertices around the zygoma, zygomatic arch and mid-lateral orbit. These sex-related significant differences are found at 55.12% of all vertices and the statistically age-related significant differences are depicted between the three age groups at a majority of all vertices (73.31% for males and 63.43% for females). Five non-overlapping categories are given and the descriptive statistics (i.e., mean, standard deviation, local standard deviation and percentage) are reported. Multiple appearances are produced using the densely calculated FSTT of various age and sex groups, and a quantitative assessment is provided to examine how relevant the choice of FSTT is to increasing the accuracy of CFR. In conclusion, this study provides a new perspective in understanding the distribution of FSTT and the construction of a new densely calculated FSTT database for craniofacial reconstruction.

3D scanning modeling method application in ancient city reconstruction

With the development of optical engineering technology, the precision of 3D scanning equipment becomes higher, and its role in 3D modeling is getting more distinctive. This paper proposed a 3D scanning modeling method that has been successfully applied in Chinese ancient city reconstruction. On one hand, for the existing architectures, an improved algorithm based on multiple scanning is adopted. Firstly, two pieces of scanning data were rough rigid registered using spherical displacers and vertex clustering method. Secondly, a global weighted ICP (iterative closest points) method is used to achieve a fine rigid registration. On the other hand, for the buildings which have already disappeared, an exemplar-driven algorithm for rapid modeling was proposed. Based on the 3D scanning technology and the historical data, a system approach was proposed for 3D modeling and virtual display of ancient city.

An automatic positioning algorithm for archaeological fragments

One of the main challenges on digital preservation of cultural heritage is to reassemble broken fragments. However, large amounts of fragments are mixed randomly when discovered, which brings terrific difficulties for their reassembly. This paper introduces an automatic approach for positioning large mixed archaeological fragments which come from a particular kind of artifact. The main idea is to position fragments based on partial matching between fragments and a complete artifact model using the multi-scale, informative and robust Heat Kernel Signature. The positioning pipeline contains four steps: feature points extraction for fragments and the complete artifact model based on Heat Kernel Signature; initial matching between feature points by comparing their Heat Kernel Signature curves; wrong matches removing using a basis points driven refinement procedure and rigid transformation generating by selecting three pairs of points among the correct matching results using farthest points sampling. After these steps, archaeological fragments can be positioned to different positions compared with the template model, which provides not only the classification information, but also the accurate relative position. The main contributions of this paper are using a novel feature extraction algorithm based on Heat Kernel Signature to assist partial matching, and a basis points driven refinement procedure to remove wrong matches. The proposed algorithm has been tested on the Terracotta Warriors fragments, and the results prove the effectiveness of the proposed positioning algorithm.

Classification and reassembly of archaeological fragments

Large number of archaeological fragments are mixed up when they are excavated, which brings difficulties for their reassembly. Computer aided restoration technologies have developed greatly in recent years, and approaches nowadays assist experts in a large scale. However, there still exist large number of fragments which are not reassembled and repaired. The current approaches have some disadvantages which affect the reassembly in large scale. This is because of the particular characteristics of archaeological fragments which affect the effectiveness of the current approaches. On the one hand, the archaeological fragments are piled up when they are excavated in archaeological sites. On the other hand, the fragments are changed during the long time because of abrasion and erosion. Therefore, innovative methods for the classification and reassembly of archaeological fragments are needed urgently. In this paper, the relate work on the classification and reassembly of archaeological fragments are first presented. Then, the problems when applying current approaches are summarized. At last, a feasible plan is given in order to classify and reassemble the fragments efficiently. By intact surface segmentation and partial matching with a complete model using discriminative feature descriptors, large number of fragments can be positioned with respect to a template model. The matching results provide the classification information and can assist the reassembly of fragments.