Three-Dimensional Biplanar Reconstruction of the Scoliotic Spine for Standard Clinical Setup

Tese de Doutoramento. Engenharia Informática. Faculdade de Engenharia. Universidade do Porto. 201

Reconstruction 3D biplanaire non supervisée de la colonne vertébrale et de la cage thoracique scoliotiques par modèles statistiques

Cette thèse présente trois approches statistiques pour la reconstruction 3D de la colonne vertébrale et de la cage thoracique scoliotiques à partir de deux images radiographiques conventionnelles. Globalement, les méthodes sont basées sur l'utilisation de contours de vertèbres ou des côtes détectées dans deux images radiographiques et une connaissance géométrique a priori de nature statistique de chaque élément. La reconstruction est formulée comme un problème de minimisation de fonctions d'énergie résolues par des méthodes d'optimisation. Pour la colonne vertébrale, les méthodes sont validées par comparaison avec des reconstructions de 57 vertèbres scoliotiques reconstruites à partir d'images tomodensitométriques. Plusieurs méthodes ont été proposées afin de raffiner les solutions obtenues et de rendre les méthodes non supervisées

Scaled, patient-specific 3D vertebral model reconstruction based on 2D lateral fluoroscopy

Backgrounds: Accurate three-dimensional (3D) models of lumbar vertebrae are required for image-based 3D kinematics analysis. MRI or CT datasets are frequently used to derive 3D models but have the disadvantages that they are expensive, time-consuming or involving ionizing radiation (e.g., CT acquisition). An alternative method using 2D lateral fluoroscopy was developed. Materials and methods: A technique was developed to reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image and a statistical shape model of the lumbar vertebrae. Four cadaveric lumbar spine segments and two statistical shape models were used for testing. Reconstruction accuracy was determined by comparison of the surface models reconstructed from the single lateral fluoroscopic images to the ground truth data from 3D CT segmentation. For each case, two different surface-based registration techniques were used to recover the unknown scale factor, and the rigid transformation between the reconstructed surface model and the ground truth model before the differences between the two discrete surface models were computed. Results: Successful reconstruction of scaled surface models was achieved for all test lumbar vertebrae based on single lateral fluoroscopic images. The mean reconstruction error was between 0.7 and 1.6mm. Conclusions: A scaled, patient-specific surface model of the lumbar vertebra from a single lateral fluoroscopic image can be synthesized using the present approach. This new method for patient-specific 3D modeling has potential applications in spine kinematics analysis, surgical planning, and navigatio

Reconstruction 3D personnalisée de la colonne vertébrale à partir d'images radiographiques non-calibrées

Les systèmes de reconstruction stéréo-radiographique 3D -- La colonne vertébrale -- La scoliose idiopathique adolescente -- Évolution des systèmes de reconstruction 3D -- Filtres de rehaussement d'images -- Techniques de segmentation -- Les méthodes de calibrage -- Les méthodes de reconstruction 3D -- Problématique, hypothèses, objectifs et méthode générale -- Three-dimensional reconstruction of the scoliotic spine and pelvis from uncalibrated biplanar X-ray images -- A versatile 3D reconstruction system of the spine and pelvis for clinical assessment of spinal deformities -- Simulation experiments -- Clinical validation -- A three-dimensional retrospective analysis of the evolution of spinal instrumentation for the correction of adolescent idiopathic scoliosis -- Auto-calibrage d'un système à rayons-X à partir de primitives de haut niveau -- Segmentation de la colonne vertébrale -- Approche hiérarchique d'auto-calibrage d'un système d'acquisition à rayons-X -- Personalized 3D reconstruction of the scoliotic spine from hybrid statistical and X-ray image-based models -- Validation protocol

Interlandmark measurements from lodox statscan images with application to femoral neck anteversion assessment

Includes abstract.Includes bibliographical references.Clinicians often take measurements between anatomical landmarks on X-ray radiographs for diagnosis and treatment planning, for example in orthopaedics and orthodontics. X-ray images, however, overlap three-dimensional internal structures onto a two-dimensional plane during image formation. Depth information is therefore lost and measurements do not truly reflect spatial relationships. The main aim of this study was to develop an inter-landmark measurement tool for the Lodox Statscan digital radiography system. X-ray stereophotogrammetry was applied to Statscan images to enable three-dimensional point localization for inter-landmark measurement using two-dimensional radiographs. This technique requires images of the anatomical region of interest to be acquired from different perspectives as well as a suitable calibration tool to map image coordinates to real world coordinates. The Statscan is suited to the technique because it is capable of axial rotations for multiview imaging. Three-dimensional coordinate reconstruction and inter-landmark measurements were taken using a planar object and a dry pelvis specimen in order to assess the intra-observer measurement accuracy, reliability and precision. The system yielded average (X, Y, Z) coordinate reconstruction accuracy of (0.08 0.12 0.34) mm and resultant coordinate reconstruction accuracy within 0.4mm (range 0.3mm – 0.6mm). Inter-landmark measurements within 2mm for lengths and 1.80 for angles were obtained, with average accuracies of 0.4mm (range 0.0mm – 2.0 mm) and 0.30 (range 0.0 – 1.8)0 respectively. The results also showed excellent overall precision of (0.5mm, 0.10) and were highly reliable when all landmarks were completely visible in both images. Femoral neck anteversion measurement on Statscan images was also explored using 30 dry right adult femurs. This was done in order to assess the feasibility of the algorithm for a clinical application. For this investigation, four methods were tested to determine the optimal landmarks for measurement and the measurement process involved calculation of virtual landmarks. The method that yielded the best results produced all measurements within 10 of reference values and the measurements were highly reliable with very good precision within 0.10. The average accuracy was within 0.40 (range 0.10 –0.80).In conclusion, X-ray stereophotogrammetry enables accurate, reliable and precise inter-landmark measurements for the Lodox Statscan X-ray imaging system. The machine may therefore be used as an inter-landmark measurement tool for routine clinical applications

Development and Validation of a Markerless Radiostereometric Analysis (RSA)System

A markerless radiostereometric analysis (RSA) system was developed to measure three- dimensional (3D) skeletal kinematics using biplanar fluoroscopy. A virtual set-up was created, in which the fluoroscope foci and image planes were positioned. Computed tomography (CT) was used to create 3D bone models that were imported into the virtual set-up and manually moved until their projections, as viewed from the two foci, matched the two images. The accuracy of the markerless RSA system in determining relative shoulder kinematic translations and orientations was evaluated against the “gold standards” of a precisions cross-slide table and a standard RSA system, respectively. Average root mean squared errors (RMSEs) of 0.082 mm and 1.18° were found. In an effort to decrease subject’s radiation exposure, the effect of lowering CT dosage on markerless RSA accuracy was evaluated. Acceptable accuracies were obtained using bone models derived from one-ninth of the normal radiation dose

Assessment of Normal Knee Kinematics Using High-Speed Stereo-Radiography System

The measurement of dynamic joint kinematics in vivo is important in order to understand the effects of joint injuries and diseases as well as for evaluating the treatment effectiveness. Quantification of knee motion is essential for assessment of joint function for diagnosis of pathology, such as tracking and progression of osteoarthritis and evaluation of outcome following conservative or surgical treatment. Total knee arthroplasty (TKA) is an invasive treatment for arthritic pain and functional disability and it is used for deformed joint replacement with implants in order to restore joint alignment. It is important to describe knee kinematics in healthy individuals for comparison in diagnosis of pathology and understanding treatment to restore normal function. However measuring the in vivo dynamic biomechanics in 6 degrees of freedom with an accuracy that is acceptable has been shown to be technically challenging. Skin marker based methods, commonly used in human movement analysis, are still prone to large errors produced by soft tissue artifacts. Thus, great deal of research has been done to obtain more accurate data of the knee joint by using other measuring techniques like dual plane fluoroscopy. The goal of this thesis is to use high-speed stereo radiography (HSSR) system for measuring joint kinematics in healthy older adults performing common movements of daily living such as straight walking and during higher demand activities of pivoting and step descending in order to establish a useful baseline for the envelope of healthy knee motion for subsequent comparison with patients with TKA. Prior to data collection, validation and calibration techniques as well as dose estimations were mandatory for the successful accomplishment of this study

The computation of blood flow waveforms from digital X-ray angiographic data

This thesis investigates a novel technique for the quantitative measurement of pulsatile blood flow waveforms and mean blood flow rates using digital X-ray angiographic data. Blood flow waveforms were determined following an intra-arterial injection of contrast material. Instantaneous blood velocities were estimated by generating a 'parametric image' from dynamic X-ray angiographic images in which the image grey-level represented contrast material concentration as a function of time and true distance in three dimensions along a vessel segment. Adjacent concentration-distance profiles in the parametric image of iodine concentration versus distance and time were shifted along the vessel axis until a match occurred. A match was defined as the point where the mean sum of the squares of the differences between the two profiles was a minimum. The distance translated per frame interval gave the instantaneous contrast material bolus velocity. The technique initially was validated using synthetic data from a computer simulation of angiographic data which included the effect of pulsatile blood flow and X-ray quantum noise. The data were generated for a range of vessels from 2 mm to 6 mm in diameter. Different injection techniques and their effects on the accuracy of blood flow measurements were studied. Validation of the technique was performed using an experimental phantom of blood circulation, consisting of a pump, flexible plastic tubing, the tubular probe of an electromagnetic flowmeter and a solenoid to simulate a pulsatile flow waveform which included reverse flow. The technique was validated for both two- and three-dimensional representations of the blood vessel, for various flow rates and calibre sizes. The effects of various physical factors were studied, including the distance between injection and imaging sites and the length of artery analysed. Finally, this method was applied to clinical data from femoral arteries and arteries in the head and neck

3D Shape Reconstruction of Knee Bones from Low Radiation X-ray Images Using Deep Learning

Understanding the bone kinematics of the human knee during dynamic motions is necessary to evaluate the pathological conditions, design knee prosthesis, orthosis and surgical treatments such as knee arthroplasty. Also, knee bone kinematics is essential to assess the biofidelity of the computational models. Kinematics of the human knee has been reported in the literature either using in vitro or in vivo methodologies. In vivo methodology is widely preferred due to biomechanical accuracies. However, it is challenging to obtain the kinematic data in vivo due to limitations in existing methods. One of the several existing methods used in such application is using X-ray fluoroscopy imaging, which allows for the non-invasive quantification of bone kinematics. In the fluoroscopy imaging method, due to procedural simplicity and low radiation exposure, single-plane fluoroscopy (SF) is the preferred tool to study the in vivo kinematics of the knee joint. Evaluation of the three-dimensional (3D) kinematics from the SF imagery is possible only if prior knowledge of the shape of the knee bones is available. The standard technique for acquiring the knee shape is to either segment Magnetic Resonance (MR) images, which is expensive to procure, or Computed Tomography (CT) images, which exposes the subjects to a heavy dose of ionizing radiation. Additionally, both the segmentation procedures are time-consuming and labour-intensive. An alternative technique that is rarely used is to reconstruct the knee shape from the SF images. It is less expensive than MR imaging, exposes the subjects to relatively lower radiation than CT imaging, and since the kinematic study and the shape reconstruction could be carried out using the same device, it could save a considerable amount of time for the researchers and the subjects. However, due to low exposure levels, SF images are often characterized by a low signal-to-noise ratio, making it difficult to extract the required information to reconstruct the shape accurately. In comparison to conventional X-ray images, SF images are of lower quality and have less detail. Additionally, existing methods for reconstructing the shape of the knee remain generally inconvenient since they need a highly controlled system: images must be captured from a calibrated device, care must be taken while positioning the subject's knee in the X-ray field to ensure image consistency, and user intervention and expert knowledge is required for 3D reconstruction. In an attempt to simplify the existing process, this thesis proposes a new methodology to reconstruct the 3D shape of the knee bones from multiple uncalibrated SF images using deep learning. During the image acquisition using the SF, the subjects in this approach can freely rotate their leg (in a fully extended, knee-locked position), resulting in several images captured in arbitrary poses. Relevant features are extracted from these images using a novel feature extraction technique before feeding it to a custom-built Convolutional Neural Network (CNN). The network, without further optimization, directly outputs a meshed 3D surface model of the subject's knee joint. The whole procedure could be completed in a few minutes. The robust feature extraction technique can effectively extract relevant information from a range of image qualities. When tested on eight unseen sets of SF images with known true geometry, the network reconstructed knee shape models with a shape error (RMSE) of 1.91± 0.30 mm for the femur, 2.3± 0.36 mm for the tibia and 3.3± 0.53 mm for the patella. The error was calculated after rigidly aligning (scale, rotation, and translation) each of the reconstructed shape models with the corresponding known true geometry (obtained through MRI segmentation). Based on a previous study that examined the influence of reconstructed shape accuracy on the precision of the evaluation of tibiofemoral kinematics, the shape accuracy of the proposed methodology might be adequate to precisely track the bone kinematics, although further investigation is required

Book of Abstracts 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization

In this edition, the two events will run together as a single conference, highlighting the strong connection with the Taylor & Francis journals: Computer Methods in Biomechanics and Biomedical Engineering (John Middleton and Christopher Jacobs, Eds.) and Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (JoãoManuel R.S. Tavares, Ed.). The conference has become a major international meeting on computational biomechanics, imaging andvisualization. In this edition, the main program includes 212 presentations. In addition, sixteen renowned researchers will give plenary keynotes, addressing current challenges in computational biomechanics and biomedical imaging. In Lisbon, for the first time, a session dedicated to award the winner of the Best Paper in CMBBE Journal will take place. We believe that CMBBE2018 will have a strong impact on the development of computational biomechanics and biomedical imaging and visualization, identifying emerging areas of research and promoting the collaboration and networking between participants. This impact is evidenced through the well-known research groups, commercial companies and scientific organizations, who continue to support and sponsor the CMBBE meeting series. In fact, the conference is enriched with five workshops on specific scientific topics and commercial software.info:eu-repo/semantics/draf