A novel and efficient implementation of the marching cubes algorithm

Total elbow arthroplasty using an augmented reality-assisted surgical technique

BACKGROUND

Precision placement of implants in total elbow arthroplasty (TEA) using conventional surgical techniques can be difficult and riddled with errors. Modern technologies such as augmented reality (AR) and 3-dimensional (3D) printing have already found useful applications in many fields of medicine. We proposed a cutting-edge surgical technique, augmented reality total elbow arthroplasty (ARTEA), that uses AR and 3D printing to provide 3D information for intuitive preoperative planning. The purpose of this study was to evaluate the accuracy of humeral and ulnar component placement using ARTEA.

METHODS

Twelve upper extremities from human frozen cadavers were used for experiments performed in this study. We scanned the extremities via computed tomography prior to performing TEA to plan placement sites using computer simulations. The ARTEA technique was used to perform TEA surgery on 6 of the extremities, whereas conventional (non-ARTEA) techniques were used on the other 6 extremities. Computed tomography scanning was repeated after TEA completion, and the error between the planned and actual placements of humeral and ulnar components was calculated and compared.

RESULTS

For humeral component placement, the mean positional error ± standard deviation of ARTEA vs. non-ARTEA was 1.4° ± 0.6° vs. 4.4° ± 0.9° in total rotation (P = .002) and 1.5 ± 0.6 mm vs. 8.6 ± 1.3 mm in total translation (P = .002). For ulnar component placement, the mean positional error ± standard deviation of ARTEA vs. non-ARTEA was 5.5° ± 3.1° vs. 19.5° ± 9.8° in total rotation (P = .004) and 1.5 ± 0.4 mm vs. 6.9 ± 1.6 mm in total translation (P = .002). Both rotational accuracy and translational accuracy were greater for joint components replaced using the ARTEA technique compared with the non-ARTEA technique (P < .05).

CONCLUSION

Compared with conventional surgical techniques, ARTEA had greater accuracy in prosthetic implant placement when used to perform TEA.

ANINet: a deep neural network for skull ancestry estimation

BACKGROUND

Ancestry estimation of skulls is under a wide range of applications in forensic science, anthropology, and facial reconstruction. This study aims to avoid defects in traditional skull ancestry estimation methods, such as time-consuming and labor-intensive manual calibration of feature points, and subjective results.

RESULTS

This paper uses the skull depth image as input, based on AlexNet, introduces the Wide module and SE-block to improve the network, designs and proposes ANINet, and realizes the ancestry classification. Such a unified model architecture of ANINet overcomes the subjectivity of manually calibrating feature points, of which the accuracy and efficiency are improved. We use depth projection to obtain the local depth image and the global depth image of the skull, take the skull depth image as the object, use global, local, and local + global methods respectively to experiment on the 95 cases of Han skull and 110 cases of Uyghur skull data sets, and perform cross-validation. The experimental results show that the accuracies of the three methods for skull ancestry estimation reached 98.21%, 98.04% and 99.03%, respectively. Compared with the classic networks AlexNet, Vgg-16, GoogLenet, ResNet-50, DenseNet-121, and SqueezeNet, the network proposed in this paper has the advantages of high accuracy and small parameters; compared with state-of-the-art methods, the method in this paper has a higher learning rate and better ability to estimate.

CONCLUSIONS

In summary, skull depth images have an excellent performance in estimation, and ANINet is an effective approach for skull ancestry estimation.

Benchmarking Various Radiomic Toolkit Features While Applying the Image Biomarker Standardization Initiative toward Clinical Translation of Radiomic Analysis

The image biomarkers standardization initiative (IBSI) was formed to address the standardization of extraction of quantifiable imaging metrics. Despite its effort, there remains a lack of consensus or established guidelines regarding radiomic feature terminology, the underlying mathematics and their implementation across various software programs. This creates a scenario where features extracted using different toolboxes cannot be used to build or validate the same model leading to a non-generalization of radiomic results. In this study, IBSI-established phantom and benchmark values were used to compare the variation of the radiomic features while using 6 publicly available software programs and 1 in-house radiomics pipeline. All IBSI-standardized features (11 classes, 173 in total) were extracted. The relative differences between the extracted feature values from the different software programs and the IBSI benchmark values were calculated to measure the inter-software agreement. To better understand the variations, features are further grouped into 3 categories according to their properties: 1) morphology, 2) statistic/histogram and 3)texture features. While a good agreement was observed for a majority of radiomics features across the various tested programs, relatively poor agreement was observed for morphology features. Significant differences were also found in programs that use different gray-level discretization approaches. Since these software programs do not include all IBSI features, the level of quantitative assessment for each category was analyzed using Venn and UpSet diagrams and quantified using two ad hoc metrics. Morphology features earned lowest scores for both metrics, indicating that morphological features are not consistently evaluated among software programs. We conclude that radiomic features calculated using different software programs may not be interchangeable. Further studies are needed to standardize the workflow of radiomic feature extraction.

THREE-DIMENSIONAL RECONSTRUCTION BASED ON IMPROVED MARCHING CUBES ALGORITHM

Based on the standard Marching Cubes (MC) algorithm, this paper proposes an improved MC algorithm. First, the original 15 topological configurations in the MC algorithm are increased to 24, which effectively avoid the generation of voids phenomenon. To further improve the speed of three-dimensional (3D) reconstruction, in this paper, the midpoint selection method is used instead of the linear interpolation method, and the 24 configurations are divided into three types. Each class corresponds to a thread. The multi-thread parallel processing is used to improve the calculation speed. The critical region is used to realize multi-thread synchronization, and then we designed a protocol mapping table according to the idea of the message mapping table. The function pointer is triggered by macro. Processing function is called by function pointer and completes the encapsulation of the protocol mapping table, which maintains the opening and closing principle of the class and ensures the scalability of the class. Through the improved MC algorithm accuracy verification and reconstruction speed verification, it is concluded that the improved MC algorithm can make up for the voids problem. By comparing the calculation time under the two platforms of Windows and Linux, the reconstruction speed of the improved MC algorithm is approximately 30% faster than the standard MC algorithm and 40% faster than the Masala algorithm. Finally, the algorithm is applied to the medical image 3D reconstruction system, and the accuracy and applicability of the algorithm are demonstrated by two sets of examples.

The relationship between the midpoints connecting the tibial attachments of the anterior and posterior cruciate ligaments and the transepicondylar axis: In vivo three-dimensional measurement in the Chinese population

BACKGROUND

To determine the relationship between the midpoints connecting the tibial attachments of the anterior and posterior cruciate ligament (ACL and PCL, APCL line) and the transepicondylar axis (TEA) in normal healthy Chinese, as well as the comparison with other rotational lines.

METHODS

Left knees of 17 male and 15 female healthy Chinese volunteers were scanned by magnetic resonance imaging (MRI) and computer tomography (CT) respectively. 3D contours of each knee, the tibial attachments of ACL, PCL, the medial and lateral collateral ligaments were reconstructed separately from CT and MRI data. Using an iterative closest point algorithm, we superimposed them individually. The APCL line, the tibial posterior condylar line (PC line), the medial third of the tibial tubercle (1/3 line), the Akagi's line, and the midsulcus of the tibial spine (Midsulcus line), the clinical and surgical TEA (CTEA and STEA) were determined. The paired intersection angles of them were measured.

RESULTS

The mean angle CTEA with APCL line, Akagi's line, Midsulcus line, 1/3 line, and PC line, respectively, was 90.3°±2.9°, 95.0°±3.0°, 94.0°±3.9°, 102.4°±2.7°, and 87.1°±3.0°. The APCL-CTEA was significant different than other angles (p<0.001). The mean angle STEA to the above lines, respectively, was 94.8°±3.1°, 99.4°±3.1°, 98.5°±4.0°, 106.9°±2.9°, and 91.6°±3.2°. The PC line-STEA was significantly different than other angles (p<0.05).

CONCLUSIONS

APCL line was the closest perpendicular to the CTEA in normal Chinese subjects comparing with other rotational lines.

Functionality, growth and accelerated aging of tissue engineered living autologous vascular grafts

Living autologous tissue engineered vascular-grafts (TEVGs) with growth-capacity may overcome the limitations of contemporary artificial-prostheses. However, the multi-step in vitro production of TEVGs requires extensive ex vivo cell-manipulations with unknown effects on functionality and quality of TEVGs due to an accelerated biological age of the cells. Here, the impact of biological cell-age and tissue-remodeling capacity of TEVGs in relation to their clinical long-term functionality are investigated. TEVGs were implanted as pulmonary-artery (PA) replacements in juvenile sheep and followed for up to 240 weeks (∼4.5years). Telomere length and telomerase activity were compared amongst TEVGs and adjacent native tissue. Telomerase-activity of in vitro expanded autologous vascular-cells prior to seeding was <5% as compared to a leukemic cell line, indicating biological-aging associated with decreasing telomere-length with each cellular-doubling. Up to 100 weeks, the cells in the TEVGs had consistently shorter telomeres compared to the native counterpart, whereas no significant differences were detectable at 240 weeks. Computed tomography (CT) analysis demonstrated physiological wall-pressures, shear-stresses, and flow-pattern comparable to the native PA. There were no signs of degeneration detectable and continuous native-analogous growth was confirmed by vessel-volumetry. TEVGs exhibit a higher biological age compared to their native counterparts. However, despite of this tissue engineering technology related accelerated biological-aging, growth-capacity and long-term functionality was not compromised. To the contrary, extensive in-vivo remodeling processes with substantial endogenous cellular turnover appears to result in "TEVG rejuvenation" and excellent clinical performance. As these large-animal results can be extrapolated to approximately 20 human years, this study suggests long-term clinical-safety of cardiovascular in vitro tissue engineering and may contribute to safety-criteria as to first-in-man clinical-trials.

A novel multithreshold method for nodule detection in lung CT

Multislice computed tomography (MSCT) is a valuable tool for lung cancer detection, thanks to its ability to identify noncalcified nodules of small size (from about 3 mm). Due to the large number of images generated by MSCT, there is much interest in developing computer-aided detection (CAD) systems that could assist radiologists in the lung nodule detection task. A complete multistage CAD system, including lung boundary segmentation, regions of interest (ROIs) selection, feature extraction, and false positive reduction is presented. The selection of ROIs is based on a multithreshold surface-triangulation approach. Surface triangulation is performed at different threshold values, varying from a minimum to a maximum value in a wide range. At a given threshold value, a ROI is defined as the volume inside a connected component of the triangulated isosurface. The evolution of a ROI as a function of the threshold can be represented by a treelike structure. A multithreshold ROI is defined as a path on this tree, which starts from a terminal ROI and ends on the root ROI. For each ROI, the volume, surface area, roundness, density, and moments of inertia are computed as functions of the threshold and used as input to a classification system based on artificial neural networks. The method is suitable to detect different types of nodules, including juxta-pleural nodules and nodules connected to blood vessels. A training set of 109 low-dose MSCT scans made available by the Pisa center of the Italung-CT trial and annotated by expert radiologists was used for the algorithm design and optimization. The system performance was tested on an independent set of 23 low-dose MSCT scans coming from the Pisa Italung-CT center and on 83 scans made available by the Lung Image Database Consortium (LIDC) annotated by four expert radiologists. On the Italung-CT test set, for nodules having a diameter greater than or equal to 3 mm, the system achieved 84% and 71% sensitivity at false positive/scan rates of 10 and 4, respectively. For nodules having a diameter greater than or equal to 4 mm, the sensitivities were 97% and 80% at false positive/scan rates of 10 and 4, respectively. On the LIDC data set, the system achieved a 79% sensitivity at a false positive/scan rate of 4 in the detection of nodules with a diameter greater than or equal to 3 mm that have been annotated by all four radiologists.

Image post-processing based on 64-slice helical CT sectional images: three-dimensional reconstruction and virtual endoscopy of large intestine

AIM: To find a method to reconstruct a large intestine three-dimensional digital model and virtual endoscopic examination based on 64-slice helical CT image in personal computer.

METHODS: We used Philips/Brilliance 64 CT to complete plain scan from the 9th thoracic vertebra to middle-femur and continuously tracked scan of arterial phase and venous phase. Based on the CT plain scan after air pressure enema, we used the VGL 3.2 sharewares to carry on the volume rendering of intestine with the Ray-Casting light projection algorithm. Mimics software for the surface was used to render intestines with the Marching Cubes algorithm then three dimensional graphics were reconstructed using virtual endoscopy (VE). We reconstructed three-dimensional large intestine and surrounding structures with the Mimics software separately based on the CTA two-dimensional graphics.

RESULTS: We have established a more precise model of volume rendering and surface rendering of large intestine and surrounding structures, including skeletal system, arterial system, urinary tract, skin, large intestine and part of small intestine. We have achieved a three-dimensional interactive browsing and virtual endoscopic applications.

CONCLUSION: The large intestine visualization model could show precisely complex anatomical structure and spatial adjoining relations, which not only offers clinic doctors reliable anatomical information, but also a good base for later virtual surgery.

Local hull-based surface construction of volumetric data from silhouettes

The marching cubes (MC) is a general method which can construct a surface of an object from its volumetric data generated using a shape from silhouette method. Although MC is efficient and straightforward to implement, a MC surface may have discontinuity even though the volumetric data is continuous. This is because surface construction is more sensitive to image noise than the construction of volumetric data. To address this problem, we propose a surface construction algorithm which aggregates local surfaces constructed by the 3-D convex hull algorithm. Thus, the proposed method initially classifies local convexities from imperfect MC vertices based on sliced volumetric data. Experimental results show that continuous surfaces are obtained from imperfect silhouette images of both convex and nonconvex objects.

A computational framework for approximating boundary surfaces in 3-D biomedical images

We propose a new method for detecting and approximating the boundary surfaces in three-dimensional (3-D) biomedical images. Using this method, each boundary surface in the original 3-D image is normalized as a zero-value isosurface of a new 3-D image transformed from the original 3-D image. A novel computational framework is proposed to perform such an image transformation. According to this framework, we first detect boundary surfaces from the original 3-D image and compute discrete samplings of the boundary surfaces. Based on these discrete samplings, a new 3-D image is constructed for each boundary surface such that the boundary surface can be well approximated by a zero-value isosurface in the new 3-D image. In this way, the complex problem of reconstructing boundary surfaces in the original 3-D image is converted into a task to extract a zero-value isosurface from the new 3-D image. The proposed technique is not only capable of adequately reconstructing complex boundary surfaces in 3-D biomedical images, but it also overcomes vital limitations encountered by the isosurface-extracting method when the method is used to reconstruct boundary surfaces from 3-D images. The performances and advantages of the proposed computational framework are illustrated by many examples from different 3-D biomedical images.

Anatomical structure modeling from medical images

Some clinical applications, such as surgical planning, require volumetric models of anatomical structures represented as a set of tetrahedra. A practical method of constructing anatomical models from medical images is presented. The method starts with a set of contours segmented from the medical images by a clinician and produces a model that has high fidelity with the contours. Unlike most modeling methods, the contours are not restricted to lie on parallel planes. The main steps are a 3D Delaunay tetrahedralization, culling of non-object tetrahedra, and refinement of the tetrahedral mesh. The result is a high-quality set of tetrahedra whose surface points are guaranteed to match the original contours. The key is to use the distance map and bit volume structures that were created along with the contours. The method is demonstrated on computed tomography, MRI and 3D ultrasound data. Models of 170,000 tetrahedra are constructed on a standard workstation in approximately 10s. A comparison with related methods is also provided.

Three-dimensional display and arbitrary region interactive segmentation of high-resolution virus capsids from cryo-electron microscopy single particle reconstruction

Recent advances in cryo-electron microscopy (cryo-EM) instrumentation and single particle reconstruction have created opportunities for high-throughput and high-resolution three-dimensional (3-D) structure determination of virus. In order to visualize and effectively understand the 3-D structure, we present a display method based on surface rendering, which has the function of 3-D arbitrary region interactive segmentation and quantitative analysis, and integrate them into a software package called CEM-3DVDSS (cryo-EM 3-D virus display and arbitrary region segmentation system). CEM-3DVDSS consists of a complete set of modular programs for 3-D display and segmentation of icosahedral virus, which is organized under a graphical user interface and provides user-friendly options. First, we convert volume data in the MRC format obtained by cryo-EM single particle reconstruction to the format of our own software; in the preprocessing step, the original volume data are compressed and a better vector dimension is found for controlling the speed and detail of display. Then, the new volume data can be displayed and segmented using CEM-3DVDSS. We demonstrate the applicability of CEM-3DVDSS by displaying the 3-D structures of 2.5 nm (resolution) BmCPV (Bombyx mori cytoplasmic polyhedrosis virus), 2.5 nm CSBV (Chinese Sacbrood bee virus) and 1.4 nm C6/36DNV (Densonucleosis virus). As a result, both the 3-D display speed and signal-to-noise ratio of CEM-3DVDSS are improved compared with the original method, and the segmentation results become precise and more intact with additional function of quantitative analysis of 3-D structure.

Automatic colon segmentation with dual scan CT colonography

We present a fully automated three-dimensional (3-D) segmentation algorithm to extract the colon lumen surface in CT colonography. Focusing on significant-size polyp detection, we target at an efficient algorithm that maximizes overall colon coverage, minimizes the extracolonic components, maintains local shape accuracy, and achieves high segmentation speed. Two-dimensional (2-D) image processing techniques are employed first, resulting in automatic seed placement and better colon coverage. This is followed by near-air threshold 3-D region-growing using an improved marching-cubes algorithm, which provides fast and accurate surface generation. The algorithm constructs a well-organized vertex-triangle structure that uniquely employs a hash table method, yielding an order of magnitude speed improvement. We segment two scans, prone and supine, independently and with the goal of improved colon coverage. Both segmentations would be available for subsequent polyp detection systems. Segmenting and analyzing both scans improves surface coverage by at least 6% over supine or prone alone. According to subjective evaluation, the average coverage is about 87.5% of the entire colon. Employing near-air threshold and elongation criteria, only 6% of the data sets include extracolonic components (EC) in the segmentation. The observed surface shape accuracy of the segmentation is adequate for significant-size (6 mm) polyp detection, which is also verified by the results of the prototype detection algorithm. The segmentation takes less than 5 minutes on an AMD 1-GHz single-processor PC, which includes reading the volume data and writing the surface results. The surface-based segmentation algorithm is practical for subsequent polyp detection algorithms in that it produces high coverage, has a low EC rate, maintains local shape accuracy, and has a computational efficiency that makes real-time polyp detection possible. A fully automatic or computer-aided polyp detection system using this technique is likely to benefit future colon cancer early screening.

Pore-scale investigation of viscous coupling effects for two-phase flow in porous media

Recent studies have revealed that viscous coupling effects in immiscible two-phase flow, caused by momentum transfer between the two fluid phases, can be important in porous medium systems. In this work, we use a three-dimensional parallel processing version of a two-fluid-phase lattice Boltzmann (LB) model to investigate this phenomenon. A multiple-relaxation-time (MRT) approximation of the LB equations is used in the simulator, which leads to a viscosity-independent velocity field. We validate our model by verifying the velocity profile for two-phase flow through a channel with a square cross section. We then simulate co-current flow through a sphere-pack porous medium and obtain correlations of the relative permeabilities as a function of capillary number, wettability, and the fluid viscosities. The results are qualitatively consistent with experimental observations. In addition, we calculate the generalized permeability coefficients and show that the coupling coefficients are significant and the matrix is nonsymmetric. We also find a strong correlation between the relative permeability and interfacial area between fluids, indicating that both the common extension of Darcy's Law and the generalized formulation accounting for viscous coupling effects do not provide adequate insight into two-phase flow processes in porous media. This work lends additional support for the hypothesis that interfacial area is a key variable for multiphase flow in porous medium systems.

Volume Manipulations for Simulating Bone and Joint Surgery

Bone and joint surgery is widely used in orthopedic, oral, and maxillofacial, and dental and plasty departments to correct bone and joint pathology such as bone and joint tumors and fractures, and skeletal morphological deformities. This article presents a voxel structure to represent topologically and geometrically correct surfaces and algorithms to accurately compute intersections of tool swept surfaces with bones based on this voxel structure. This article then presents various volume manipulation algorithms to operate on virtual bones, bone grafts, and prostheses for bone and joint surgery simulations. A complicated knee arthroplasty illustrates the practicality and versatility of the proposed method.

Automatic spinal disease diagnoses assisted by 3D unaligned transverse CT slices

This paper describes a three-dimensional (3D) reconstruction method and an automatic diagnosis method for spinal diseases using unaligned transverse slices that have arbitrary angles and intervals but do not intersect to each other at regions of interest. The 3D reconstruction method extends the marching cube algorithm to generate triangulated isosurfaces for these unaligned slices. The automatic spinal disease diagnostic method analyses boundaries of discs and vertebral bodies on unaligned transverse slices to estimate the presence and extent of disc herniation and canal compression, and deformities in the spinal curve. The prototype system can be used as a qualitative and quantitative tool for the diagnosis of various spinal diseases using unaligned transverse slices.

Marching cube algorithm: review and trilinear interpolation adaptation for image-based dosimetric models

Current internal organ dose assessment methodologies utilize three-dimensional (3D) medical images of the body to model organ shapes and tissue interfaces. These models are coupled to computer programs that measure radionuclide energy deposition or chord-length distributions directly within these images. Previous studies have shown that the rectangular shape of image voxels generates voxel effects that alter the outcome of these calculations. To minimize voxel effects, the present study proposes to use the Marching Cube (MC) algorithm to generate isosurfaces delineating tissue interfaces from the gray-level images. First, a review of the different techniques surrounding the MC algorithm is presented. Next, an adaptation of the algorithm is proposed in which a trilinear interpolation of the gray levels is used to generate a hyperboloid surface within the MCs. This new technique is shown to solve the classic ambiguity problem of the MC algorithm and also to reduce the data size inherent to the triangulated surface. It also provides a simple algorithm to accurately measure distances within the image. The technique is then tested with a mathematical model of trabecular bone. The trilinear interpolation method is shown to remove voxel effects and to produce reliable chord-length distributions across image regions. The technique is thus recommended for use with digital medical images needed for internal radiation transport simulations. The current study is performed for a single isosurface that separates two media within the same image, but it is proposed that the technique can be extended to multiple isosurfaces that delineate several organs or organ regions within 3D tomographic voxels of human anatomy.

Modeling tumor growth and irradiation response in vitro--a combination of high-performance computing and web-based technologies including VRML visualization

A simplified three-dimensional Monte Carlo simulation model of in vitro tumor growth and response to fractionated radiotherapeutic schemes is presented in this paper. The paper aims at both the optimization of radiotherapy and the provision of insight into the biological mechanisms involved in tumor development. The basics of the modeling philosophy of Duechting have been adopted and substantially extended. The main processes taken into account by the model are the transitions between the cell cycle phases, the diffusion of oxygen and glucose, and the cell survival probabilities following irradiation. Specific algorithms satisfactorily describing tumor expansion and shrinkage have been applied, whereas a novel approach to the modeling of the tumor response to irradiation has been proposed and implemented. High-performance computing systems in conjunction with Web technologies have coped with the particularly high computer memory and processing demands. A visualization system based on the MATLAB software package and the virtual-reality modeling language has been employed. Its utilization has led to a spectacular representation of both the external surface and the internal structure of the developing tumor. The simulation model has been applied to the special case of small cell lung carcinoma in vitro irradiated according to both the standard and accelerated fractionation schemes. A good qualitative agreement with laboratory experience has been observed in all cases. Accordingly, the hypothesis that advanced simulation models for the in silico testing of tumor irradiation schemes could substantially enhance the radiotherapy optimization process is further strengthened. Currently, our group is investigating extensions of the presented algorithms so that efficient descriptions of the corresponding clinical (in vivo) cases are achieved.