Novel geometric coordination registration in cone-beam computed tomogram

Paper ID: AIPR-140701-9The use of cone-beam computed tomography (CBCT) in medical field can help the clinicians to visualize the hard tissues in head and neck region via a cylindrical field of view (FOV). The images are usually presented with reconstructed three-dimensional (3D) imaging and its orthogonal (x-, y-and z-planes) images. Spatial relationship of the structures in these orthogonal views is important for diagnosis of diseases as well as planning for treatment. However, the non-standardized positioning of the object during the CBCT data acquisition often induces errors in measurement since orthogonal images cut at different planes might look similar. In order to solve the problem, this paper proposes an effective mapping from the Cartesian coordinates of a cube physically to its respective coordinates in 3D imaging. Therefore, the object (real physical domain) and the imaging (computerized virtual domain) can be linked up and registered. In this way, the geometric coordination of the object/imaging can be defined and its orthogonal images would be fixed on defined planes. The images can then be measured with vector information and serial imagings can also be directly compared. © 2014 IEEE.published_or_final_versio

Validation of a novel geometric coordination registration using manual and semi-automatic registration in cone-beam computed tomogram

Session - Image Processing: Machine Vision Applications 9Cartesian coordinates define on a physical cubic corner (CC) with the corner tip as the origin and three corresponding line angles as (x, y, z)-axes. In its image (virtual) domains such as these obtained by cone-beam computed tomography (CBCT) and optical surface scanning, a single coordinate can then be registered based on the CC. The advantage of using a CC in registration is simple and accurate physical coordinate measurement. The accuracy of image-to-physical (IP) and imageto-image (II) transformations, measured by target registration error (TRE), can then be validated by comparing coordinates of target points in the virtual domains to that of the physical control. For the CBCT, the registration may be performed manually using a surgical planning software SimPlant Pro (manual registration (MR)) or semi-automatically using MeshLab and 3D Slicer (semiautomatic registration (SR)) matching the virtual display axes to the corresponding (x-y-z)-axes. This study aims to validate the use of CC as a surgical stereotactic marker by measuring TRE in MR and SR respectively. Mean TRE is 0.56 +/- 0.24 mm for MR and 0.39 +/- 0.21 mm for SR. The SR results in a more accurate registration than the MR and point-based registration with 20 fiducial points. TRE of the MR is less than 1.0 mm and still acceptable clinically.postprin

Image calibration and registration in cone-beam computed tomogram for measuring the accuracy of computer-aided implant surgery

Medical radiography is the use of radiation to “see through” a human body without breaching its integrity (surface). With computed tomography (CT)/cone beam computed tomography (CBCT), three-dimensional (3D) imaging can be produced. These imagings not only facilitate disease diagnosis but also enable computer-aided surgical planning/navigation. In dentistry, the common method for transfer of the virtual surgical planning to the patient (reality) is the use of surgical stent either with a preloaded planning (static) like a channel or a real time surgical navigation (dynamic) after registration with fiducial markers (RF). This paper describes using the corner of a cube as a radiopaque fiducial marker on an acrylic (plastic) stent, this RF allows robust calibration and registration of Cartesian (x, y, z)- coordinates for linking up the patient (reality) and the imaging (virtuality) and hence the surgical planning can be transferred in either static or dynamic way. The accuracy of computer-aided implant surgery was measured with reference to coordinates. In our preliminary model surgery, a dental implant was planned virtually and placed with preloaded surgical guide. The deviation of the placed implant apex from the planning was x=+0.56mm [more right], y=- 0.05mm [deeper], z=-0.26mm [more lingual]) which was within clinically 2mm safety range. For comparison with the virtual planning, the physically placed implant was CT/CBCT scanned and errors may be introduced. The difference of the actual implant apex to the virtual apex was x=0.00mm, y=+0.21mm [shallower], z=-1.35mm [more lingual] and this should be brought in mind when interpret the results

Multi-scale imaging of porous media and flow simulation at the pore scale

In the last decade, the fundamental understanding of pore-scale flow in porous media has been undergoing a revolution through the recent development of new pore-scale imaging techniques, reconstruction of three-dimensional pore space images, and advances in the computational methods for solving complex fluid flow equations directly or indirectly on the reconstructed three-dimensional pore space images. Important applications include hydrocarbon recovery from - and CO2 storage in - reservoir rock formations. Of particular importance is the consideration of carbonate reservoirs, as our understanding of carbonates with respect to geometry and fluid flow processes is still very limited in comparison with sandstone reservoirs. This thesis consists of work mainly performed within the Qatar Carbonates and Carbon Storage Research Centre (QCCSRC) project, focusing on development of three dimensional imaging techniques for accurately characterizing and predicting flow/transport properties in both complex benchmark carbonate and sandstone rock samples. Firstly, the thesis presents advances in the application of Confocal Laser Scanning Microscopy (CLSM), including the improvement of existing sample preparation techniques and a step-by step guide for imaging heterogeneous rock samples exhibiting sub-micron resolution pores. A novel method has been developed combining CLSM with sequential grinding and polishing to obtain deep 3D pore-scale images. This overcomes a traditional limitation of CLSM, where the depth information in a single slice is limited by attenuation of the laser light. Other features of this new method include a wide field of view at high resolution to arbitrary depth; fewer grinding steps than conventional serial sectioning using 2D microscopy; the image quality does not degrade with sample size, as e.g. in micro-computed tomography (micro- CT) imaging. Secondly, it presents two fundamental issues – Representative Element of Volume (REV) and scale dependency which are addressed with qualitative and quantitative solutions for rocks increasing in heterogeneity from beadpacks to sandpacks to sandstone to carbonate rocks. The REV is predicted using the mathematical concept of the Convex Hull, CH, and the Lorenz coefficient, LC, to investigate the relation between two macroscopic properties simultaneously, in this case porosity and absolute permeability. The effect of voxel resolution is then studied on the segmented macro-pore phase (macro-porosity) and intermediate phase (micro-porosity) and the fluid flow properties of the connected macro-pore space using lattice-Boltzmann (LB) and pore network (PN) modelling methods. A numerical coarsening (up-scaling) algorithm have also been applied to reduce the computational power and time required to accurately predict the flow properties using the LB and PN methods. Finally, a quantitative methodology has been developed to predict petrophysical properties, including porosity and absolute permeability for X-ray medical computed tomography (CT) carbonate core images of length 120 meters using image based analysis. The porosity is calculated using a simple segmentation based on intensity grey values and the absolute permeability using the Kozeny-Carman equation. The calculated petrophysical properties were validated with the experimental plug data.Open Acces

AUGMENTED REALITY AND INTRAOPERATIVE C-ARM CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED ROBOTIC SURGERY

Minimally-invasive robotic-assisted surgery is a rapidly-growing alternative to traditionally open and laparoscopic procedures; nevertheless, challenges remain. Standard of care derives surgical strategies from preoperative volumetric data (i.e., computed tomography (CT) and magnetic resonance (MR) images) that benefit from the ability of multiple modalities to delineate different anatomical boundaries. However, preoperative images may not reflect a possibly highly deformed perioperative setup or intraoperative deformation. Additionally, in current clinical practice, the correspondence of preoperative plans to the surgical scene is conducted as a mental exercise; thus, the accuracy of this practice is highly dependent on the surgeon’s experience and therefore subject to inconsistencies. In order to address these fundamental limitations in minimally-invasive robotic surgery, this dissertation combines a high-end robotic C-arm imaging system and a modern robotic surgical platform as an integrated intraoperative image-guided system. We performed deformable registration of preoperative plans to a perioperative cone-beam computed tomography (CBCT), acquired after the patient is positioned for intervention. From the registered surgical plans, we overlaid critical information onto the primary intraoperative visual source, the robotic endoscope, by using augmented reality. Guidance afforded by this system not only uses augmented reality to fuse virtual medical information, but also provides tool localization and other dynamic intraoperative updated behavior in order to present enhanced depth feedback and information to the surgeon. These techniques in guided robotic surgery required a streamlined approach to creating intuitive and effective human-machine interferences, especially in visualization. Our software design principles create an inherently information-driven modular architecture incorporating robotics and intraoperative imaging through augmented reality. The system's performance is evaluated using phantoms and preclinical in-vivo experiments for multiple applications, including transoral robotic surgery, robot-assisted thoracic interventions, and cocheostomy for cochlear implantation. The resulting functionality, proposed architecture, and implemented methodologies can be further generalized to other C-arm-based image guidance for additional extensions in robotic surgery

Integrating Deep Learning into Digital Rock Analysis Workflow

Digital Rock Analysis (DRA) has expanded our knowledge about natural phenomena in various geoscience specialties. DRA as an emerging technology has limitations including (1) the trade-off between the size of spatial domain and resolution, (2) methodological and human-induced errors in segmentation, and (3) the computational costs associated with intensive modeling. Deep learning (DL) methods are utilized to alleviate these limitations. First, two DL frameworks are utilized to probe the performance gains from using Convolutional Neural Networks (CNN) to super-resolve and segment real multi-resolution X-ray images of complex carbonate rocks. The first framework experiments the applications of U-Net and U-ResNet architectures to obtain macropore, solid, and micropore segmented images in an end-to-end scheme. The second framework segregates the super-resolution and segmentation into two networks: EDSR and U-ResNet. Both frameworks show consistent performance indicated by the voxel-wise accuracy metrics, the measured phase morphology, and flow characteristics. The end-to-end frameworks are shown to be superior to using a segregated approach confirming the adequacy of end-to-end learning for performing complex tasks. Second, CNNs accuracy margins in estimating physical properties of porous media 2d X-ray images are investigated. Binary and greyscale sandstone images are used as an input to CNNs architectures to estimate porosity, specific surface area, and average pore size of three sandstone images. The results show encouraging margins of accuracy where the error in estimating these properties can be up to 6% when using binary images and up to 7% when using greyscale images. Third, the suitability of CNNs as regression tools to predict a more challenging property, permeability, is investigated. Two complex CNNs architectures (ResNet and ResNext) are applied to learn the morphology of pore space in 3D porous media images for flow-based characterization. The dataset includes more than 29,000 3d subvolumes of multiple sandstone and carbonates rocks. The findings show promising regression accuracy using binary images. Accuracy gains are observed using conductivity maps as an input to the networks. Permeability inference on unseen samples can be achieved in 120 ms/sample with an average relative error of 18.9%. This thesis demonstrates the significant potential of deep learning in improving DRA capabilities

Micro- and nanoanatomy of human brain tissues

“Better to see something once than to hear about it a thousand times.” Proverb The human brain is one of the most complex organs in the body, containing billions of neurons of hundreds of types. To understand its properties and functionality at the most fundamental level, one must reveal and describe its structure down to the(sub-)cellular level. In general, three-dimensional (3D) characterisation of physically soft tissues is a challenge. Thus, the possibility of performing non-destructive label-free 3D imaging with the reasonable sensitivity, resolution and increased manageable specimen sizes, especially within the laboratory environment, is of great interest. The focus of the thesis relies on the non-destructive 3D investigation of the micro and nanoanatomy of human brain tissues. The ambitious challenge faced was to bridge the performance gap between the tomography data from laboratory systems, histological approaches employed by anatomists and pathologists, and synchrotron radiation-based tomography, by taking advantage of recent developments in X-ray tomographic imaging. The main reached milestones of the project include (i) visualisation of individual Purkinje cells in a label-free manner by laboratory-based absorption-contrast micro computed tomography (LBμCT), (ii) incorporation of the double-grating interferometer into the nanotom® m (GE Sensing & Inspection Technologies GmbH, Wunstorf, Germany) for phase-contrast imaging and (iii) visualisation and quantification of sub-cellular structures using nano-holotomography (nano-imaging beamline ID16A-NI, European ynchrotron Radiation Facility (ESRF), Grenoble, France). Hard X-ray micro computed tomography (μCT) in the absorption-contrast mode is well-established for hard tissue visualisation. However, performance in relation to lower density materials, such as post mortem brain tissues, is questionable, as attenuation differences between anatomical features are weak. It was demonstrated, through the example of a formalin-fixed paraffin-embedded (FFPE) human cerebellum, that absorption-contrast laboratory-based micro computed tomography can provide premium contrast images, complementary to hematoxylin and eosin (H&E) stained histological sections. Based on our knowledge, the detection of individual Purkinje cells without a dedicated contrast agent is unique in the field of absorption-contrast laboratory-based micro computed tomography. As the intensity of H&E staining of histological sections and the attenuation contrast of LBμCT data demonstrated a correlation, pseudo colouring of tomography data according to the H&E stain can be performed, virtually extending two-dimensional (2D) histology into the third dimension. The LBμCT of FFPE samples can be understood as a time-efficient and reliable tissue visualisation methodology, and so it could become a method of choice for imaging of relatively large specimens within the laboratory environment. Comparing the data acquired at the LBμCT system nanotom® m and synchrotron radiation facilities (Diamond-Manchester Imaging Branchline I13-2, Diamond Light Source, Didcot, UK and Microtomography beamline ID19, ESRF), it was demonstrated that all selected modalities, namely LBμCT, synchrotron radiation-based in line phase-contrast tomography using single-distance phase reconstruction and synchrotron radiation-based grating interferometry, can reach cellular resolution. As phase contrast yields better data quality for soft tissues, and in order to overcome the restrictions of limited beamtime access for phase-contrast measurements,a commercially available advanced μCT system nanotom® m was equipped with an X-ray double-grating interferometer (XDGI). The successful performance of the interferometer in the tomography mode was demonstrated on a human knee joint sample. XDGI provided enough contrast (1.094 ± 0.152) and spatial resolution (73 ± 6) μm to identify the cartilage layer, which is not recognised in the absorption mode without staining. These results suggest that the extension of a commercially available absorption-contrast μCT system via grating interferometry offers the potential to fill the performance gap between LBμCT and phase-contrast μCT using synchrotron radiation in the visualising soft tissues. Although optical microscopy of stained tissue sections enables the quantification of neuron morphology within brain tissues in health and disease, the lateral spatial resolution of histological sections is limited to the wavelength of visible light, while the orthogonal resolution is usually restricted to the section´s thickness. Based on the data acquired from the ID16A-NI, the study demonstrated the application of hard X-ray nano-holotomography with isotropic voxels down to 25 nm for the three dimensional visualising the human cerebellum and neocortex. The images exhibit a reasonable contrast to noise ratio and a spatial resolution of at least 84 nm. Therefore, the three dimensional data resembles the surface images obtained by electron microscopy (EM), but in this case electron dense staining is avoided. The (sub-)cellular structures within the Purkinje, granule, stellate and pyramidal cells of the FFPE tissue blocks were resolved and segmented. Micrometre spatial resolution is routinely achieved at synchrotron radiation facilities worldwide, while reaching the isotropic 100-nm barrier for soft tissues without applying any dedicated contrast agent, labelling or tissue-transformation is a challenge that could set a new standard in non-destructive 3D imaging

Crystal Cartography: Mapping Nanostructure with Scanning Electron Diffraction

Nanostructure describes the network of defective and distorted atomic structure existing on the nanoscale within materials. This nanostructure bridges the gap between idealised crys- talline structure and real materials, playing a deterministic role in tailoring physico-chemical properties, as well as providing a basis for mechanistic understanding of complex processes such as mechanical deformation and phase transformation. Characterising nanostructure, to develop understanding of materials, requires experimental techniques capable of probing the structure with spatial resolution on the order of nanometres and across regions of interest up to micrometres. Recent developments in electron microscopy, enabling the acquisition of numerous diffraction patterns in a spatially resolved manner, combined with modern computational power, provides a route to meet this need as developed in this work. Scanning electron diffraction (SED) involves the acquisition of a two-dimensional elec- tron diffraction pattern at each probe position in a two-dimensional scan of a specimen. An information rich 4-dimensional (4D-SED) dataset is obtained that can be analysed extensively post-facto using a wide-range of computational methods. The acquisition of such 4D-SED data from the specimen at numerous orientations may also enable the reconstruction of nanostructure in three-dimensions via tomographic methods. In this work, methods for the acquisition and analysis of 4D-SED data are developed and applied to reveal nanostructure in two and three-dimensions. These methods are applied to various prototypical characterisation challenges in materials science, particularly: strain mapping in two and three dimensions, revealing inter-phase crystallographic relationships, mapping grains in two-dimensional materials, and probing nanostructure in polyethylene

Investigation of materials for catalysis with electron tomography

Elektronentomographie mit dem Transmissionselektronenmikroskop (TEM) ermöglicht die Erstellung dreidimensionaler Darstellungen (Tomogramme) von Proben in der Größenordnung von einigen Nanometern bis hin zu einigen Mikrometern. Im Rahmen dieser Arbeit wurden verschiedene auf Ruthenium basierende Werkstoffe für die Katalyse in Brennstoffzellen untersucht. Die Tomographie liefert, im Gegensatz zu gewöhnlichen TEM Bildern (Projektionen), Aufschluss über die Verteilung und Erreichbarkeit der Katalysatorpartikel auf bzw. in dem Trägermaterial. Es konnte gezeigt werden, dass neben qualitativen Vergleichen der Verteilung der Rutheniumpartikel auf/in dem Kohleträgermaterial verschieden hergestellter Proben auch detaillierte quantitative Analysen möglich sind. Da die Katalyse an heterogenen Katalysatoren an der Oberfläche des Katalysators stattfindet, spielen neben der Größe der Oberfläche auch die unterschiedlichen Koordinationszahlen verschieden orientierter Facetten der Katalysatorpartikel eine Rolle. Dazu wurde erstmalig ein Algorithmus entwickelt, der es erlaubt, viele verschiedene Partikel in dreidimensionalen Datensätzen automatisch hinsichtlich Facettierung zu analysieren. Durch die teilweise Einbettung der Katalysatorpartikel in das Trägermaterial ist eine Unterscheidung der bedeckten und unbedeckten Oberfläche nötig, da nur der unbedeckte Teil der Katalysatoroberfläche von den Reaktanten erreicht werden kann. Neben dieser unbedeckten Oberfläche ist durch die teilweise Einbettung auch die Ausrichtung der Katalysatorpartikel in Bezug zur lokalen Oberfläche des Trägers bedeutsam, da so statistische Untersuchungen der unbedeckten Facettentypen möglich werden. Zu den durchgeführten Charakterisierungen wie: Partikelverteilung innerhalb des Trägers, Größenverteilung, Oberflächen, Volumina, Formanalyse und der lokalen Ausrichtung, wurden Erkenntnisse gewonnen, die es erlauben, den untersuchten Katalysatortyp während der Herstellung weiter zu optimieren. Es konnte zudem gezeigt werden, dass die entwickelten Bildanalysemethoden sich auch auf tomographische Datensätze anderer Messmethoden wie z.B. Neutronen- und Focused Ion Beam-Tomographie anwenden lassen.Electron tomography with a transmission electron microscope (TEM) enables creation of three-dimensional representations (tomograms) of samples in the range of a few nanometres to a few micrometres. In the frame of this thesis different ruthenium-based materials for catalysis in fuel cells were investigated. Tomography, in contrast to common TEM images (projections), yields information about the distribution and accessibility of the catalyst particles on or in the support material. It was shown that in addition to qualitative comparisons of the distribution of ruthenium particles on/in the carbon support material of differently manufactured samples, quantitative analyses are also possible. Since catalysis on heterogeneous catalysts takes place at the surface of the catalyst, the amount of surface area matters as do the coordination numbers of differently oriented facets of the catalyst particles. For this purpose a new algorithm was developed that allows to automatically analyse faceting of many different particles in a three-dimensional dataset. Due to the partial embedding of the catalyst particles into the support material only the uncovered fraction of the catalyst surface is accessible to the reactants and therefore a differentiation between the covered and uncovered catalyst surface is necessary. Apart from this uncovered surface, the orientation of the catalyst particles relative to the local support surface is also important since this allows statistical investigation of the uncovered facet types. In addition to the conducted characterizations such as: particle distribution within the support, size distribution, surface areas, volumes, shape analysis and the local orientation, new insights were gained which allow optimization of the examined catalyst during production. Furthermore, it could be shown that the developed image analysis methods can be applied to tomographic datasets from other measurement techniques such as neutron and focused ion beam tomography

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society