Volume Reconstruction Research Articles

Calibration of 3D scan trajectories for an industrial computed tomography setup with 6-DOF object manipulator system using a single sphere

In industrial x-ray computed tomography (CT), the application of more complex scan paths in comparison to the typical circular trajectory ( rotation of the measurement object) can extend the potential of CT. One way to enable such 3D scan trajectories is to use a 6-degrees-of-freedom (DOF) object manipulator system. In our case, a hexapod is mounted on top of the rotary table of a commercial CT scanner. This allows for adaptive tilting of the measurement object during the scan. For high accuracy, the geometry calibration of such setups is typically done using the x-ray projections of a calibrated multi-sphere object. Contrary to this, here, we demonstrate a procedure that is based on only a single sphere and can therefore experimentally be implemented with low effort. Using the intrinsic geometry parameters of the CT device as prior information, the hexapod coordinate system with respect to the CT machine coordinate system is determined by means of a one-step optimization approach. The resulting parameters are used to calculate projection matrices that enable the volume reconstruction for 3D scan trajectories. The method is validated using simulated x-ray images and experimental investigations including dimensional measurements. For the used setup, geometric measurement results for 3D scan trajectories that are calibrated with the presented method show in sum increased errors compared to the circular scans. A limited pose accuracy of the manipulator system is discussed as a potential cause. The results nevertheless indicate that the presented method is generally feasible for dimensional CT measurements provided that the pose accuracy is sufficient. The calibration procedure can therefore be a low-cost and easier to implement alternative compared to trajectory calibration methods based on multi-sphere objects, but with a tendency towards lower measurement accuracy. The methodology can in principle be transferred to different setups with 6-DOF manipulator systems, e.g. C-arm CT devices with a robot arm.

ADJUST: a dictionary-based joint reconstruction and unmixing method for spectral tomography

Advances in multi-spectral detectors are causing a paradigm shift in x-ray computed tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material composition maps of the object of interest. If the materials and their spectral responses are known a priori, the image reconstruction step is rather straightforward. If they are not known, however, the maps as well as the responses need to be estimated jointly. A conventional workflow in spectral CT involves performing volume reconstruction followed by material decomposition, or vice versa. However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem. To resolve this issue, we propose ‘A Dictionary-based Joint reconstruction and Unmixing method for Spectral Tomography’ (ADJUST). Our formulation relies on forming a dictionary of spectral signatures of materials common in CT and prior knowledge of the number of materials present in an object. In particular, we decompose the spectral volume linearly in terms of spatial material maps, a spectral dictionary, and the indicator of materials for the dictionary elements. We propose a memory-efficient accelerated alternating proximal gradient method to find an approximate solution to the resulting bi-convex problem. From numerical demonstrations on several synthetic phantoms, we observe that ADJUST performs exceedingly well compared to other state-of-the-art methods. Additionally, we address the robustness of ADJUST against limited and noisy measurement patterns. The demonstration of the proposed approach on a spectral micro-CT dataset shows its potential for real-world applications. Code is available at https://github.com/mzeegers/ADJUST.

Reconstruction of ovine axonal cytoarchitecture enables more accurate models of brain biomechanics

There is an increased need and focus to understand how local brain microstructure affects the transport of drug molecules directly administered to the brain tissue, for example in convection-enhanced delivery procedures. This study reports a systematic attempt to characterize the cytoarchitecture of commissural, long association and projection fibres, namely the corpus callosum, the fornix and the corona radiata, with the specific aim to map different regions of the tissue and provide essential information for the development of accurate models of brain biomechanics. Ovine samples are imaged using scanning electron microscopy combined with focused ion beam milling to generate 3D volume reconstructions of the tissue at subcellular spatial resolution. Focus is placed on the characteristic cytological feature of the white matter: the axons and their alignment in the tissue. For each tract, a 3D reconstruction of relatively large volumes, including a significant number of axons, is performed and outer axonal ellipticity, outer axonal cross-sectional area and their relative perimeter are measured. The study of well-resolved microstructural features provides useful insight into the fibrous organization of the tissue, whose micromechanical behaviour is that of a composite material presenting elliptical tortuous tubular axonal structures embedded in the extra-cellular matrix. Drug flow can be captured through microstructurally-based models using 3D volumes, either reconstructed directly from images or generated in silico using parameters extracted from the database of images, leading to a workflow to enable physically-accurate simulations of drug delivery to the targeted tissue.

Experimental Improvements to the Volume Ratio and Quantifying Movement Using Stone Artefact Analysis

Many conceptual frameworks of archaeological assemblages have assumed that stone artefact assemblages include all products of manufacture, use, and discard, although recent studies have indicated this is not always the case. The volume ratio is a method that examines the potential for the removal or addition of stone artefacts to an assemblage after manufacture. As humans transport material, and the movement of material effects the composition of assemblages, the alteration of an assemblage through the addition or removal of material can act as a proxy for mobility. This research uses three experimental assemblages to test the effect that different methods of volume quantification and reconstruction have on the calculation of the volume ratio. Results suggest observed assemblage volume is accurately and efficiently calculated using a standardised density of 2.46 g/cm³, while the modelled assemblage volume is relatively accurately calculated using either the Volumetric Reconstruction Method (VRM) or the Flake Volumetric Reconstruction Method (FVRM) with the potential for future research to further improve this methodology.

Ultra-High Molecular Weight Polyethylene (marPOR) is a Suitable Material for the Reconstruction of Orbital Floor Fracture Defects in Human Cadavers

Abstract Purpose Despite there being different materials for orbital floor reconstruction available today, outcomes are still not satisfying. In recent years, ultra-high molecular weight polyethylene (UHMWPE) has gained popularity in the field of orthopedic surgery due to its good biocompatibility and low infection rate. With its three-dimensional compound structure, it combines high stability and ductility, making it a potential material to be used for orbital floor reconstruction. Methods In a cadaver study, an overall of eighteen orbits were included. Fractures of the inferior wall were induced and then reconstructed using Polyglactin 910/PDS composite (Ethisorb) and UHMWPE (marPOR). Orbits were scanned by cone-beam CT in each condition: Intact, fractured and reconstructed with Ethisorb, marPOR 0.85 mm and marPOR 1.5 mm. Segmented orbital volumes were calculated by specialized software (Disior bonelogic CMF). Results All materials led to sufficient reconstruction of the initial orbital volumes (Ethisorb: p < 0.001; marPOR 0.85 mm: p = 0.003; marPOR 1.5 mm: p < 0.001). Orbits that were reconstructed with marPOR 0.85 mm showed the least mean volume difference from intact orbital volumes. Conclusion UHMWPE (marPOR) offers reliable reconstruction of orbital floor fractures combined with good stability, ductility and biocompatibility.

Improved failure analysis in scanning acoustic microscopy via advanced signal processing techniques

With the upcoming semiconductor devices, becoming more and more complex, also the failure analysis becomes more challenging. Advanced signal processing methods can improve the abilities of scanning acoustic microscopy significantly. On the one hand, they can reduce the measurement effort, on the other hand, they can improve detection capabilities.In contrast to conventional imaging, which requires each layer needs to be scanned separately, this paper proposes the application of synthetic aperture focusing technique to the scan data. By superposing the signals of several scan positions a virtual, much larger aperture is generated. This allows a reconstruction of the full volume and provides information about structures in any depths. Reconstruction is done in time domain and frequency domain. The method is applied on a reference sample and real microelectronic samples are examined.Especially for structures with a huge number of interfaces and a periodic structure the signal to noise ratio is very low for the deeper interfaces. Wavelet transform using fast Mexican hat and its coefficient selection filtering techniques are used for improving the SNR and by this enhancing defect detection. The method is demonstrated on a reference sample and on high bandwidth memory modules consist of a stack of small memory dies.

Improved topography reconstruction of volume scattering objects using structured light.

The use of structured light projection enables the reconstruction of three-dimensional topography of surface reflecting objects. However, if the investigated object exhibits volume scattering, the obtained topography is erroneously caused by light undergoing volume scattering inside the object. In this theoretical study, we investigate these errors using Monte Carlo simulations. Additionally, a method is proposed to correct the errors by quantifying the light propagation in the scattering object based on the radiative transfer equation. Reconstructed surfaces with a small spatial variation of topography can be quickly corrected using a local correction method that depends only on the directions of the incident and detected light relative to the surface. For surfaces that show a large spatial variation of the surface geometry, another approach is introduced by simulating the light propagation in the whole scanned three-dimensional object using graphics processing unit (GPU)-accelerated Monte Carlo simulations. A cylindrical object and an incisor tooth are, exemplarily, investigated. The results show a major improvement in the reconstructed topography due to the correction with the proposed methods.

A new camera model combining an analytical model and a discrete correction to overcome refractive index variation challenges

When performing Tomo-PIV experiments, the calculation of accurate camera models is a key point for successful measurements. In severe configurations, where optical interfaces are involved and refractive index variations occur along the line of sight, analytical models can fail to accurately represent the projection and back-projection functions. This inability can lead to significant inaccuracies in particle location and volume reconstruction, which has a considerable impact on the calculation of velocity fields. In order to overcome these limitations, an innovative camera model based on the combination of an analytical model, such as a pinhole model or a polynomial model, with discrete corrections is proposed. In this method, the analytical projection and back-projection are adjusted with a discrete correction stored in two adaptive grids that save both memory and computation time. These correction grids require calibration which is performed with triangulation procedures similar to those used in misalignment corrections. The calculation and operation of the model are described in this paper. The performance of the camera model is evaluated on simulated and experimental setups based on a large depth-of-field calibration performed in a glass water tank. The presence of multiple optical interfaces and fluids, resulting in large light deviations, makes it difficult to compute a high accuracy camera model. In this configuration, the proposed technique successfully reduces the triangulation error from 1 pixel to less than 0.01 pixel. The usefulness of the model is demonstrated in a Tomo-PIV experiment where the deflection of light through the water tunnel walls prevents classical analytical functions from accurately modelling the projection and back-projection functions. This corrected model can also solve discontinuity problems in the projection functions and can be used when there are interfaces in the measurement volume. It opens new perspectives in the study of fluid-structure interaction when transparent solids are involved.

Expected affine: A registration method for damaged section in serial sections electron microscopy.

Registration is essential for the volume reconstruction of biological tissues using serial section electron microscope (ssEM) images. However, due to environmental disturbance in section preparation, damage in long serial sections is inevitable. It is difficult to register the damaged sections with the common serial section registration method, creating significant challenges in subsequent neuron tracking and reconstruction. This paper proposes a general registration method that can be used to register damaged sections. This method first extracts the key points and descriptors of the sections to be registered and matches them via a mutual nearest neighbor matcher. K-means and Random Sample Consensus (RANSAC) are used to cluster the key points and approximate the local affine matrices of those clusters. Then, K-nearest neighbor (KNN) is used to estimate the probability density of each cluster and calculate the expected affine matrix for each coordinate point. In clustering and probability density calculations, instead of the Euclidean distance, the path distance is used to measure the correlation between sampling points. The experimental results on real test images show that this method solves the problem of registering damaged sections and contributes to the 3D reconstruction of electronic microscopic images of biological tissues. The code of this paper is available at https://github.com/TongXin-CASIA/Excepted_Affine.

Dual-energy fast neutron imaging using tunable short-pulse laser-driven sources.

A novel dual-energy fast neutron imaging technique is presented using short-pulse laser-driven neutron sources to leverage their inherent adaptive spectral control to enable 3D volume segmentation and reconstruction. Laser-accelerated ion beams incident onto secondary targets create directional, broadband, MeV-class neutrons. Synthetic radiographs are produced of multi-material objects using ion and neutron spectra derived from analytic and numerical models. It is demonstrated that neutron images generated from small changes to the neutron spectra, controlled by altering the initial laser conditions, are sufficient to isolate materials with differing attenuation coefficients. This is first demonstrated using a simplistic combinatorial isolation method and then by employing more advanced reconstruction algorithms to reduce artifacts and generate a segmentation volume of the constituent materials.

Preoperative 3D volume reconstruction of the posterior wall of the sphenoid sinus with Horos: A free, simple and reliable tool in endoscopic endonasal trans-sphenoidal surgery

The purpose of the study was to create computer-aided design models of the sphenoid sinus with a free-source software in order to perform a preoperative planning during trans-sphenoidal endoscopic surgery (TES) and clarify the three-dimensional anatomical features of the sphenoid sinus and its surrounding structures. For each patient a 3D volume rendering of the sphenoid sinus was obtained from a thin slice head and maxilla-facial CT scan using a free-source DICOM viewer. The 3D models obtained preoperatively were examined preoperatively by six neurosurgeons in order to identify the boundaries of the sella. For the main anatomical landmark, all of the observers were able to recognize the anatomical structure at a rate ranging from 80 to 98%, 28 to 60% and 25 to 58% for expert (n = 3), inexpert (n = 3) and the entire group of observers (n = 6), respectively. The analysis of the data shows that both observation groups presented a lower recognition rate of the following parameters: right and left medial and lateral optocarotid recesses and tumor prominence, however, the sellar prominence, clival recess, planum sphenoidalis, right and left ICA prominence, right and left optic prominences represent the main anatomical landmarks to be recognized during TES immediately before the opening of the sellar floor. The use of a preoperative 3D imaging is not in itself a novelty in the literature, however the fact that a simple tool obtained with a free-source software like Horos can represent a considerable help in surgical practice without resorting to the use of more complex software and expensive represents the real utility of this work. El objetivo del estudio es crear modelos de diseño asistido por ordenador del seno esfenoidal con software de código abierto para realizar la planificación preoperatoria durante la cirugía transesfenoidal endoscópica (TES) y dilucidar las características anatómicas tridimensionales del seno esfenoidal y las estructuras que lo rodean. Para cada paciente, se obtuvo una representación volumétrica en 3D del seno esfenoidal, a partir de una tomografía computarizada maxilofacial de corte fino utilizando un visor DICOM de fuente libre. Los modelos 3D obtenidos antes de la cirugía fueron revisados por seis neurocirujanos para identificar los límites de la silla turca. Para el principal punto de referencia anatómico, todos los observadores fueron capaces de reconocer la estructura anatómica en un rango de 80 a 98%, 28 a 60% y 25 a 58% para los experimentados (n = 3), los inexpertos (n = 3) y todo el grupo de observadores (n = 6), respectivamente. El análisis de los datos muestra que ambos grupos de observación presentaron una tasa de reconocimiento menor de los siguientes parámetros: recesos optocarotídeos medial y lateral izquierdo y prominencia tumoral, sin embargo, prominencia selar, receso clival, plano esfenoidal, prominencia ICA derecha e izquierda. Las prominencias ópticas derecha e izquierda representan los principales puntos de referencia anatómicos que deben reconocerse durante la TES inmediatamente antes de la apertura del suelo selar. El uso de una imagen 3D preoperatoria no es en sí mismo una novedad en la literatura, sin embargo, el hecho de que una simple herramienta obtenida con un software de código abierto como Horos pueda representar una importante ayuda en la práctica quirúrgica, sin tener que recurrir al uso de un software más complejo y costoso, representa la verdadera utilidad de este trabajo.

Preoperative 3D volume reconstruction of the posterior wall of the sphenoid sinus with Horos: A free, simple and reliable tool in endoscopic endonasal trans-sphenoidal surgery

BackgroundThe purpose of the study was to create computer-aided design models of the sphenoid sinus with a free-source software in order to perform a preoperative planning during trans-sphenoidal endoscopic surgery (TES) and clarify the three-dimensional anatomical features of the sphenoid sinus and its surrounding structures. MethodsFor each patient a 3D volume rendering of the sphenoid sinus was obtained from a thin slice head and maxilla-facial CT scan using a free-source DICOM viewer. The 3D models obtained preoperatively were examined preoperatively by six neurosurgeons in order to identify the boundaries of the sella. ResultsFor the main anatomical landmark, all of the observers were able to recognize the anatomical structure at a rate ranging from 80 to 98%, 28 to 60% and 25 to 58% for expert (n=3), inexpert (n=3) and the entire group of observers (n=6), respectively. The analysis of the data shows that both observation groups presented a lower recognition rate of the following parameters: right and left medial and lateral optocarotid recesses and tumor prominence, however, the sellar prominence, clival recess, planum sphenoidalis, right and left ICA prominence, right and left optic prominences represent the main anatomical landmarks to be recognized during TES immediately before the opening of the sellar floor. ConclusionsThe use of a preoperative 3D imaging is not in itself a novelty in the literature, however the fact that a simple tool obtained with a free-source software like Horos can represent a considerable help in surgical practice without resorting to the use of more complex software and expensive represents the real utility of this work.

Complete fully automatic detection, segmentation and 3D reconstruction of tumor volume for non-small cell lung cancer using YOLOv4 and region-based active contour model

We aim to develop a fully automatic system that will detect, segment and accurately reconstruct non-small cell lung cancer tumors into space using YOLOv4 and region-based active contour model. The system consists of two main sections which are detection and volumetric rendering. The detection section is composed of image enhancement, augmentation, labeling and localization while the volumetric rendering is mainly image filtering, tumor extraction, region-based active contour and 3D reconstruction. In this method the images are enhanced to eliminate noise before augmentation which is intended to multiply and diversify the image data. Labeling was then carried out in order to create a solid learning foundation for the localization model. Images with localized tumors were passed through smoothing filters and then clustered to extract tumor masks. Lastly contour information was obtained to render the volumetric tumor. The designed system displays a strong detection performance with a precision of 96.57%, sensitivity and F 1 score of 97.02% and 96.79% respectively at a detection speed of 34 fps, prediction time per image of 21.38 ms. The system segmentation validation achieved a dice score coefficient of 92.19 % on tumor extraction. A 99.74 % accuracy was obtained during the verification of the method’s volumetric rendering using a 3D printed image of the rendered tumor. The rendering of the volumetric tumor was obtained at an average time of 11 s. This system shows a strong performance and reliability due to its ability to detect, segment and reconstruct a volumetric tumor into space with high confidence.

Ventilation Study of the Human Lungs by 19F MRI at 0.5 Tesla

To show the feasibility of functional lung assessment by 19F MRI using low field (0.5 T) MRI scanner. One healthy volunteer participated in the studies. As a contrast for 19F pulmonary MRI, the gas mixture of 70% octafluorocyclobutane (OFCB) and 30% oxygen was used. 19F MR images of human lungs were obtained using 2D and 3D FSE methods. MRI data were used for volume reconstruction and for calculation of wash-in/-out and single-breath dynamics measurements. 19F 3D imaging provided information about gas distribution and lung volume assessment. The measured volume of the left and right parts of lungs were ≈1.7L and ≈1.8L, respectively. The wash-in/-out dynamics measurements determined that the effective time of gas washing in was 30 ± 5 s and washing out was 19 ± 4 s. Fractional ventilation was 29 ± 3% and 18 ± 2% for wash-in and wash-out processes, respectively. Dynamics of gas distribution during one breath cycle was analyzed. The calculated inspiration and expiration maps gave normalized effective times [rel. un.] for these stages- 0.95 ± 0.18 and 0.84 ± 0.15, respectively. Different 19F pulmonary MRI methods were implemented: 3D imaging, wash-in/-out dynamics and single respiratory cycle imaging. The results are agreed with known data and demonstrates possibility of ventilation assessment of the lungs at 0.5 Tesla.

Study on Key Technologies of Virtual Interactive Surgical Simulation for 3D Reconstruction of Medical Images.

Medical computed tomography (CT), nuclear magnetic resonance imaging (MRI), and other imaging facility produce a large amount of medical image data which has great diagnosis value. Traditional three-dimensional reconstruction of medical images has high requirements for graphics acceleration hardware and the processing speed. In this study, VxWorks embedded real-time process feature is used for CT or MRI DICOM data to real restoration and establishment of virtual three-dimensional model for realizing volume reconstruction, maximum density projection, multiplane reconstruction, dynamic interactive cutting of any surface, dynamic display of three-dimensional model and two-dimensional sectional image, surgical path planning and interactive surgical simulation, and determine the best surgical scheme. The practical application shows that the virtual simulation environment supports the seamless transplantation of code, function debugging, and interaction and solves the issue of high requirements for hardware. It can meet the needs of scientific research and teaching for clinicians and medical imaging workers and can be widely used in the training of virtual surgical anatomy for medical students.

A Bottom-Up Volume Reconstruction Method for Atom Probe Tomography.

This paper describes a reconstruction method for atom probe tomography based on a bottom-up approach accounting for (i) the final tip morphology (which is frequently induced by inhomogeneous evaporation probabilities across the tip surface due to laser absorption, heat diffusion effects, and inhomogeneous material properties), (ii) the limited (and changing) field of view, and (iii) the detector efficiency. The reconstruction starts from the final tip morphology and reverses the evaporation sequence through the pseudo-deposition of defined small reconstruction volumes, which are then stacked together to create the full three-dimensional (3D) tip. The subdivision in small reconstruction volumes allows the scheme to account for the changing tip shape and field of view as evaporation proceeds. Atoms within the same small reconstruction volume are reconstructed at once by placing atoms back onto their possible lattice sites through a trajectory-matching process involving simulated and experimental hit maps. As the ejected ion trajectories are simulated using detailed electrostatic modeling inside the chamber, no simplifications have been imposed on the shape of the trajectories, projection laws, or tip surface. We demonstrate the superior performance of our approach over the conventional reconstruction method (Bas) for an asymmetrical tip shape.

CryoAI: amortized inference of poses for ab initio reconstruction of 3D molecular volumes from experimental cryo-EM images

<i>CryoAI</i>: amortized inference of poses for <i>ab initio</i> reconstruction of 3D molecular volumes from experimental cryo-EM images

How innovations in methodology offer new prospects for volume electron microscopy

Detailed knowledge of biological structure has been key in understanding biology at several levels of organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, the throughput rate of conventional electron microscopes has limited the volume size and number of samples that can be imaged. Recent improvements in methodology are currently driving a revolution in volume EM, making possible the structural imaging of whole organs and small organisms. In turn, these recent developments in image acquisition have created or stressed bottlenecks in other parts of the pipeline, like sample preparation, image analysis and data management. While the progress in image analysis is stunning due to the advent of automatic segmentation and server‐based annotation tools, several challenges remain. Here we discuss recent trends in volume EM, emerging methods for increasing throughput and implications for sample preparation, image analysis and data management.

Error Estimation of the 3D Reconstruction of a Displacement Field from DIC Measurements

To enable an accurate simulation of manufacturing processes, it is essential to characterise and model the mechanical behaviour of sheet metals up to large deformations. However, after the onset of necking, deformation becomes highly heterogeneous and the stress is triaxial. By combining full-field measurements and inverse methods, it is possible to calibrate the mechanical behaviour beyond necking. A possibility is to use the virtual fields method, by extending its formulation to a fully three-dimensional approach. However, measuring deformation in the bulk of the material is still a challenge. To address this limitation, a volume reconstruction method able to estimate the deformation inside the specimen was proposed and successfully validated. The aim of this work is to estimate the error of the volume reconstruction method by using a simulated tensile test and the measurement chain associated with a virtual stereo-DIC setup composed of four cameras. A three-dimensional finite element model is used to deform synthetically generated images. The DIC field maps obtained with different setup configurations and DIC settings are used to estimate the error by comparing the reconstructed volume with the reference finite element model. Results show that the impact of conditions and DIC settings on the reconstructed volume is low.

Weighted 3D volume reconstruction from series of slice data using a modified Allen–Cahn equation

In this study, we develop a fast and accurate computational method for a weighted three-dimensional (3D) volume reconstruction from a series of slice data using a phase-field model. The proposed method is based on a modified Allen–Cahn (AC) equation with a fidelity term. The algorithm automatically generates the necessary slices between the given slices by solving the governing equation. To reconstruct a 3D volume, we first set a source slice and target slice. Next, we set the source slice as the initial condition and the target slice as the fidelity function. Finally, we retain the numerical solutions during an evolution as intermediate slices between the source and target slices. There are two criteria for choosing the intermediate slice: One is based on the area of the symmetric difference between the phase-field solution and the target and the other is based on the change of the phase-field solution relative to the area of the target. We use the weighted average of the two criteria. To validate the efficiency and accuracy of the proposed numerical algorithm, several computational experiments are conducted. Computational test results confirm the superior performance of the proposed algorithm.