Academic literature on the topic '4D Tracking'

(1) Background: the aims of this study were to determine the total extent of pancreatic cancer’s internal motions, using Calypso® extracranial tracking, and to indicate possible clinical advantages of continuous intrafractional fiducial-based tumor motion tracking during SABR. (2) Methods: thirty-four patients were treated with SABR for LAPC using Calypso® for motion management. Planning MSCTs in FB and DBH, and 4D-CTs were performed. Using data from Calypso® and 4D-CTs, the movements of the lesions in the CC, AP and LR directions, as well as the volumes of the 4D-CT-based ITV and the volumes of the Calypso®-based ITV were compared. (3) Results: significantly larger medians of tumor excursions were found with Calypso® than with 4D-CT: CC: 29 mm (p < 0.001); AP: 14 mm (p < 0.001) and LR: 11 mm (p < 0.039). The median volume of the Calypso®-based ITV was significantly larger than that of the 4D-CT based ITV (p < 0.001). (4) Conclusion: beside known respiratory-induced internal motions, pancreatic cancer seems to have significant additional motions which should be considered during respiratory motion management. Only direct and continuous intrafractional fiducial-based motion tracking seems to provide complete coverage of the target lesion with the prescribed isodose, which could allow for safe tumor dose escalation.

The LHCb experiment will enter the High Luminosity phase during the Run 4 of the LHC. In order to fully exploit the flavour opportunities of the HL-LHC, an upgrade of the detector, the LHCb Upgrade II, will be installed during the LS4 (2030), targeting an instantaneous luminosity of 1-2 10^34 cm^-2 s^-1 and aiming at collecting an integrated luminosity of 300 fb^-1. With the higher luminosity the mean number of interactions at each bunch crossing will increase up to μ ≈ 50, resulting in a significant increase of the total number of tracks per each event, and providing a challenging environment for the track reconstruction, which has to be performed in real time at the visible crossing rate of 30 MHz. The introduction of precise timing detectors will be crucial to mitigate the pile-up effects, allowing the LHCb experiment to exploit larger data samples and keep producing high quality measurements. The author presents a 4D real-time tracking device capable of reconstructing four dimensional particle tracjectories in real time using precise space and time information of the hits, to be applied to a possible Upgrade II of the VELO sub-detector. The proposed fast track finding device is implemented in commercial FPGAs with a modular and highly parallelized and pipelined architecture to work at high rates and with latency below 1 μs. The performance of the 4D fast tracking algorithm and its hardware implementation have been tested on a custom board equipped with latest generation FPGAs (Xilinx Virtex UltraScale) and high input data bandwidth (up to 1.6 Tbps). The demonstrator prototype has been tested with simulated data from a sector (∼ 1/64) of the LHCb VELO and has to be considered as a proof of principle of a large scale system able to process the full detector.

The effectiveness of cancer treatment is compromised by the need to reduce the uncertainties originating from a variety of factors including tumor volume delineation, patient setup, and irregular physiologic motion. In particular, effective yet practical tumor motion management remains a major challenge in current external beam radiation therapy. Many strategies such as motion encompassment, breath-hold techniques, and respiratory gating have been proposed in the literature and implemented clinically. These methods have shown success in certain situations with different limitations. With the advent of image guided radiation therapy, real-time tumor tracking methods have become popular in clinics to proactively address the challenge with on-board tumor localization. Nevertheless, such techniques rely on surrogate signals and have been reported vulnerable to errors. In this dissertation, EGRT is proposed as a new modality for effective and practical management strategy of cancer treatment uncertainties. One implementation of EGRT is to use PET emissions in real-time for direct tumor tracking during radiation delivery. Radiation beamlets are delivered along PET lines of response by a fast rotating ring therapy unit consisting of a linear accelerator and PET detectors. A complete treatment scheme with capabilities of accurate tumor tracking and dose planning is proposed to implement this EGRT concept. Simulation studies with physical phantom, 4D digital patient model, and clinical patient datasets are carefully designed to evaluate the feasibility and performance of EGRT. We show that with the capabilities of achieving both tumor tracking and sophisticated intensity modulation, EGRT has the potential to enable an effective implementation of 4D radiation therapy with true biological targeting and other advantages.

This thesis mainly focuses on proposing a 4D (three spatial dimensions plus time) tissue-volume preserving non-rigid image registration algorithm for pulmonary 4D computed tomography (4DCT) data sets to provide relevant information for radiation therapy and to estimate pulmonary ventilation. The sum of squared tissue volume difference (SSTVD) similarity cost takes into account the CT intensity changes of spatially corresponding voxels, which is caused by variations of the fraction of tissue within voxels throughout the respiratory cycle. The proposed 4D SSTVD registration scheme considers the entire dynamic 4D data set simultaneously, using both spatial and temporal information. We employed a uniform 4D cubic B-spline parametrization of the transform and a temporally extended linear elasticity regularization of deformation field to ensure temporal smoothness and thus biological plausibility of estimated deformation. A multi-resolution multi-grid registration framework was used with a limited-memory Broyden Fletcher Goldfarb Shanno (LBFGS) optimizer for rapid convergence rate, robustness against local minima and limited memory consumption. The algorithm was prototyped in Matlab and then fully implemented in C++ in Elastix package based on the Insight Segmentation and Registration Toolkit (ITK). We conducted experiments on 2D+t synthetic images to demonstrate the effectiveness of the proposed method. The 4D SSTVD algorithm was also tested on clinical pulmonary 4DCT data sets in comparison with existing 3D pairwise SSTVD algorithm and 4D sum of squared difference (SSD) algorithm. The mean landmark error and mean landmark irregularity were calculated based on manually annotated landmarks on publicly available 4DCT data sets to evaluate the accuracy and temporal smoothness of the registration results. A 4D landmarking software tool was also designed and implemented in Java as an ImageJ plug-in to help facilitate the landmark labeling process in 4DCT data sets.

Purpose: The main objective of this research project is to address the limitations of image-processing computational performance of current ultrasound target motion estimation techniques by developing a novel high-performance ultrasound motion estimation technique that eliminates the need for using currently adopted image-registration-based motion-estimation techniques for systems requiring ultrasound target tracking. To address the system's dependence on the operator's experience and supervision as the second objective of this research project, the developed target tracking technique is integrated with a novel automation platform developed to support medical physicists with tools for collectively implementing, supervising, and training arbitrary ultrasound target motion estimation tasks and incorporate them in the platform as reusable solutions to support qualified and reproducible research. Methodologies: The main objective of this research project has been addressed by enabling high-performance and accurate motion estimation of soft-tissue-equivalent ultrasound targets using the ultrasound direct visual servoing (US-DVS) technique for the first time. The inaccurate US-target tracking capabilities of the implemented US-DVS technique have been addressed and optimised using specially trained machine-learning models which lead to the US direct visual modelling (US-DVM) technique introduced by this project. The machine-learning models implemented by the US-DVM technique were trained using two types of US-target motion simulations: simulation of tissue-equivalent US-target motion based on predefined motion trajectories provided by high-precision robotic-arms; and simulations using an ultrasound digital-target dynamics simulator (US-DTDS) developed by this project. The second objective of this research project has been addressed by maximising the performance and target detection accuracy of the proposed motion estimation technique by minimising its dependence on the operator and by transferring the operator's target scanning and identification experience to a provenance-enabled automation system. To Achieve this, another machine-learning model, based on Gaussian mixture modelling (GMM), was also developed and used to improve the performance of standard image segmentation techniques allowing for automating target detection and tracking in real-time. In addition, the interaction of the operator with the platform has been optimised by employing a provenance-enabled workflow automation framework, called VisTrails, to implement the proposed new technique and all the supporting services required. This will help in learning the operator's skills by the automation workflow, which will minimise the operators' systematic errors and support reproducible research. Results: A Medical Physics Services Framework (MPS-F) has been developed based on VisTrails and used to control two robotic arms to track and capture the simulated motion using the US-DVM technique. The new US-DVM technique has enabled accurate estimation of ultrasound target motion from US-DVS tracking feedback with accuracies better than 1.5%, and with computational performance up to 14 times better than motion estimation techniques used in current practice. This allows for more accurate real-time tracking of ultrasound targets like the prostate. Regarding the second objective, high-performance detection and extraction of deformable ultrasound targets using the morphological active-contour technique (MACT) has been achieved for average prostate-size targets to within 0.04 seconds using down-sampling strategies. To further support the second objective, the MPS-F has been developed as a provenance-enabled software automation solution to enable other researchers to reuse and reproduce most of the implementations and results of this research, and hence minimise the operator's systematic errors. The MPS-F has been used to implement a novel technique that combined the MACT and the US-DVM to detect and estimate prostate-size target deformations with volume accuracies better than 0.005 cm^3. Conclusion: This research study introduced the US-DVM technique as a novel ultrasound target motion modelling and estimation solution based on ultrasound direct visual servoing (US-DVS). US-DVS is used typically for ultrasound target tracking in real-time and using it for modelling and estimating target dynamics has been addressed for the first time by this study based on machine learning strategies. The machine learning approach provided solutions that overcame inherent limitations of the imaging system allowing for predicting faster dynamics and larger interframe displacements, in addition to enabling supervised and automated predictions of accurate motion estimations tailored specifically for individual targets for optimal consistency and accuracy. The proposed techniques and solutions have been implemented and evaluated by the medical physics services framework (MPS-F), which was developed by this project based on the VisTrails workflow management system. The MPS-F is considered a major contribution by this study where it enables the operator to implement, train, and supervise arbitrary medical physics workflows that can employ machine-learning, image-processing, and ultrasound target tracking and motion estimation tasks. With the help of the MPF-S, it is proposed by this study that an ultrasound modelling and automation platform (US-MAP) can be constructed as a more efficient real-time alternative for the Elekta Clarity Autoscan system being the only non-telerobotic real-time ultrasound target tracking system implemented clinically for tracking prostate motion.

The present thesis deals with the study of vision techniques for the detection of human pose based on the analysis of a single image, as well as the tracking of these poses along a sequence of images. It is proposed to model the human pose by four kinematic chains that model the four articulated extremities. These kinematic chains and head remain attached to the body. The four kinematic chains are composed by three keypoints. Therefore, the model initially has a total of $14$ parts. In this thesis it is proposed to modify the technique called Deformable Parts Model (DPM), adding the depth channel. Initially, the DPM model was defined over three RGB channel images. While in this thesis it is proposed to work on images of four RGBD channels, so the proposed extension is called 4D-DPM. The experiments performed with 4D-DPM demonstrate an improvement in the accuracy of pose detection with respect to the initial DPM model, at the cost of increasing its computational cost when treating an additional channel. On the other hand, it is defined to reduce the previous computational cost by simplifying the model that defines the human pose. The idea is to reduce the number of variables to be detected with the 4D-DPM model, so that the suppressed variables can be calculated from the detected variables using inverse kinematics models based on dual quaternions. In addition, it is proposed to use a particle filter models to continue improving the accuracy of detection of human poses along a sequence of images. Considering the problem of detection and monitoring of human body pose along a video sequence, this thesis proposes the use of the following method. 1. Camara calibration. RGBD image processing. Subtraction of the image background with the MSER method. 2. 4D-DPM: method used to detect the keypoints (variables of the pose model) within an image. 3. Particle filters: this type of filter is designed to track the keypoints over time and correct the data obtained by the sensor. 4. Inverse kinematic modeling: the control of kinematic chains is performed with the help of dual cuaternions in order to obtain the complete pose model of the human body. The overall contribution of this thesis is the proposal of the previous method that, combining the previous methods, is able to improve the accuracy in the detection and the follow up of the human body pose in a video sequence, also reducing its computational cost . This is possible due to the combination of the 4D-DPM method with the use of inverse kinematics techniques. The original DPM method should detect $14$ point of interest on an RGB image to estimate the human pose. However, the proposed method, where a point of interest for each limb is removed, must detect $10$ point of interest on an RGBD image. Subsequently, the eliminated $4$ point of interest are calculated by using inverse kinematics methods from the calculated $10$ point of interest. To solve the problem of inverse kinematics a dual quaternions methods is proposed for each of the $4$ kinematic chains that model the extremities of the skeleton of the human body. The particle filter is applied over the time sequence of the 10 points of interest of the posture model detected through the 4D-DPM method. To design these particle filters it is proposed to add the following restrictions to weight the particles generated: 1. Restrictions on joint limits. 2. Softness restrictions. 3. Collision detection. 4. Projection of poly-spheres
La presente tesis trata sobre el estudio de técnicas de visión para la detección de la postura del esqueleto del cuerpo humano basada en el análisis de una sola imagen, además del seguimiento de estas posturas a lo largo de una secuencia de imágenes. Se propone modelar la postura del esqueleto cuerpo humano mediante cuatro cadenas cinemáticas que modelan las cuatro extremidades articuladas. Estas cadenas cinemáticas y la cabeza permanecen unidas al cuerpo. Las cuatro cadenas cinemáticas se componen de tres puntos de interés. Por lo tanto, el modelo inicialmente dispone de un total de 14 puntos de interés. En esta tesis se propone modificar la técnica denominada Deformable Parts Model (DPM), añadiendo el canal de profundidad denominado ``Depth''. Inicialmente el modelo DPM se definió sobre imágenes de tres canales RGB. Mientras que en esta tesis se propone trabajar sobre imágenes de cuatro canales RGBD, por ello a la ampliación propuesta se le denomina 4D-DPM. Por otra parte, se propone reducir el coste computacional anterior simplificando el modelo que define la postura del cuerpo humano. La idea es reducir el número de variables a detectar con el modelo 4D-DPM, de tal manera que las variables suprimidas se puedan calcular a partir de las variables detectadas, utilizando modelos de cinemática inversa basados en cuaterniones duales. Los experimentos realizados demuestran que la combinación de estas dos técnicas permite, reduciendo el coste computacional del método original DPM, mejorar la precisión de la detección de postura debido a la información extra del canal de profundidad. Adicionalmente, se propone utilizar modelos de filtros de partículas para continuar mejorando la precisión de la detección de las posturas humanas a lo largo de una secuencia de imágenes. Atendiendo al problema de detección y seguimiento de las postura del esqueleto del cuerpo humano a lo largo de una secuencia de vídeo, esta tesis propone el uso del siguiente método. 1. Calibración de cámaras. Procesamiento de imágenes RGBD. Sustracción del fondo de la imagen con el método MSER. 2. 4D-DPM: método utilizado para detectar los puntos de interés (variables del modelo de postura) dentro de una imagen. 3. Filtros de partículas: se diseña este tipo de filtros para realizar el seguimiento de los puntos de interés a lo largo del tiempo y corregir los datos obtenidos por el sensor. 4. Modelado cinemático inverso: se realiza el control de cadenas cinemáticas con la ayuda de cuaterniones duales con el fin de obtener el modelo completo de la postura del esqueleto del cuerpo humano. La contribución global de esta tesis es la propuesta del método anterior que, combinando los métodos anteriores, es capaz de mejorar la precisión en la detección y el seguimiento de la postura del esqueleto del cuerpo humano en una secuencia de vídeo, reduciendo además su coste computacional. El método original DPM debe detectar 14 puntos de interés sobre una imagen RGB para estimar la postura de un cuerpo humano. Sin embargo, el método propuesto debe detectar 10 puntos de interés sobre una imagen RGBD. Posteriormente, los 4 puntos de interés eliminados se calculan mediante la utilización de métodos de cinemática inversa a partir de los 10 puntos de interés calculados. Para resolver el problema de la cinemática inversa se propone utilizar cuaterniones duales para cada una de las 4 cadenas cinemáticas que modelan las extremidades del esqueleto del cuerpo humano. El filtro de partículas se aplica sobre la secuencia temporal de los 10 puntos de interés del modelo de postura detectados a través del método 4D-DPM. Para diseñar estos filtros de partículas se propone añadir las siguientes restricciones, explicadas en la memoria, para ponderar las partículas generadas: 1. Restricciones en los límites de articulaciones. 2. Restricciones de suavidad. 3. Detección de colisiones. 4. Proyección de las poli-esferas.
La present tesi tracta sobre l'estudi de tècniques de visió per a la detecció de la postura de l'esquelet del cos humà basada en l'anàlisi d'una sola imatge, a més del seguiment d'estes postures al llarg d'una seqüència d'imatges. Es proposa modelar la postura de l'esquelet del cos humà per mitjà de quatre cadenes cinemàtiques que modelen les quatre extremitats articulades. Estes cadenes cinemàtiques i el cap romanen unides al cos. Les quatre cadenes cinemàtiques es componen de tres punts d'interés. Per tant, el model inicialment disposa d'un total de $14$ punts d'interés. En esta tesi es proposa modificar la tècnica denominada Deformable Parts Model (DPM) , afegint el canal de profunditat denominat ``Depth''. Inicialment el model DPM es va definir sobre imatges de tres canals RGB. Mentres que en esta tesi es proposa treballar sobre imatges de quatre canals RGBD, per això a l'ampliació proposada se la denomina 4D-DPM. D'altra banda, es proposa reduir el cost computacional anterior simplificant el model que definix la postura del cos humà. La idea és reduir el nombre de variables a detectar amb el model 4D-DPM, de tal manera que les variables suprimides es puguen calcular a partir de les variables detectades, utilitzant models de cinemàtica inversa basats en quaternions duals. Els experiments realitzats demostren que la combinació d'estes dos tècniques permet, reduint el cost computacional del mètode original DPM, millorar la precisió de la detecció de la postura degut a la informació extra del canal de profunditat. Addicionalment, es proposa utilitzar models de filtres de partícules per a continuar millorant la precisió de la detecció de les postures humanes al llarg d'una seqüència d'imatges. Atenent al problema de detecció i seguiment de les postura de l'esquelet del cos humà al llarg d'una seqüència de vídeo, esta tesi proposa l'ús del següent mètode. 1. Calibratge de càmeres. Processament d'imatges RGBD. Sostracció del fons de la imatge amb el mètode MSER. 2. 4D-DPM: mètode utilitzat per a detectar els punts d'interés (variables del model de postura) dins d'una imatge. 3. Filtres de partícules: es dissenya este tipus de filtres per a realitzar el seguiment dels punts d'interés al llarg del temps i corregir les dades obtingudes pel sensor. 4. Modelatge cinemàtic invers: es realitza el control de cadenes cinemàtiques amb l'ajuda de quaternions duals a fi d'obtindre el model complet de l'esquelet del cos humà. La contribució global d'esta tesi és la proposta del mètode anterior que, combinant els mètodes anteriors, és capaç de millorar la precisió en la detecció i el seguiment de la postura de l'esquelet del cos humà en una seqüència de vídeo, reduint a més el seu cost computacional. Açò és possible a causa de la combinació del mètode 4D-DPM amb la utilització de tècniques de cinemàtica inversa. El mètode original DPM ha de detectar 14 punts d'interés sobre una imatge RGB per a estimar la postura d'un cos humà. No obstant això, el mètode proposat ha de detectar 10 punts d'interés sobre una imatge RGBD. Posteriorment, els 4 punts d'interés eliminats es calculen per mitjà de la utilització de mètodes de cinemàtica inversa a partir dels 10 punts d'interés calculats. Per a resoldre el problema de la cinemàtica inversa es proposa utilitzar quaternions duals per a cada una de les 4 cadenes cinemàtiques que modelen les extremitats de l'esquelet del cos humà. El filtre de partícules s'aplica sobre la seqüència temporal dels 10 punts d'interés del model de postura detectats a través del mètode 4D-DPM. Per a dissenyar estos filtres de partícules es proposa afegir les següents restriccions per a ponderar les partícules generades: 1. Restriccions en els límits d'articulacions. 2. Restriccions de suavitat. 3. Detecció de col·lisions. 4. Projecció de les poli-esferes.
Martínez Bertí, E. (2017). SEGUIMIENTO DE PERSONAS APLICANDO RESTRICCIONES CINEMÁTICAS BASADAS EN MODELOS DE CUERPOS RÍGIDOS ARTICULADOS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86159
TESIS

L'objectif était de quantifier les modifications de la contractilité cardiaque au cours d’un bedrest de 21 jours (HDBR) par la methode speckle tracking 4D et de déterminer si la contre-mesure « exercice » était capable de préserver cette contractilité cardiaque. Les méthodes traditionnelles 2D ne mesurent qu'une variation de la taille du ventricule de la systole à la diastole et ne suivent pas la cinetique des mouvements de contractilité à l’interieur de la paroi. De plus l’echographie 2D ne permet d’acceder qu’a la contractilite longitudinale globale par la mesure de la distance Apex-Valve mitrale. Le suivi des mouvements des speckles (points singuliers a l’interieur du myocarde) en 4D montre que la contractilité radiale diminuée signifcativement pendant le HDTBR chez les sujets témoins alors qu’elle est conservée dans le groupe exercice. Par contre la contractilité longitudinale n’est pas affectée dans aucun des 2 groupes. Bien sûr, l'IRM pourrait fournir des données similaires, mais il n’est pas possible à ce jour d’imaginer avoir une IRM a bord de l’ISS dans un futur proche. A la suite de ces resultats nous avons mis au point un algorithme de traitement des video cardiaque qui permet d’acceder a la contractilite radiale et longitudinale en vol (prog Vasc-Aging en cours) .L’objectif de l’experimentation était de montrer que quatre jours en immersion seche suffisaient pour realiser un transfert liquidien important vers les régions céphaliques comparable à celui observé en vol spatial. Notre protocole consistait donc a mesurer les volume veineux au niveau cervical cerebral et porte au debut de la periode en immersion (a 2h) puis a 4 jours d’immersion. Compte tenu des problemes engendrés par ce transfert liquidien en vol nous avions proposé de tester la capacité des brassarts de cuisse a reduire l’amplitude du transfert veineux. Les résultats montrent que l’immersion provoque un transfert de sang veineux au niveau cervical maximal à 2H et que les Brassarts de cuisse reduisent signifcativement ce transfert dans cette phase precoce. Par contre a 4 jours d’immersion l’amplitude du transfert sanguin est considerablement diminuée (bien que toujours presente) et les brassarts de cuisse n’ont pas d’effet visible à ce moment-là. En fait le volume plasmatique decroit significativement à la fin du premier jour (env 20%) des lors la masse de sang deplacées vers la tete par l’immersion est insuffisante pour generer une stase importante au niveau cervical comme à 2h d’immersion. Pour cette meme raison la vitesse dans les veines cerebrales n’est pas augmentée à 4 jours d’immersion contrairement à ce qu’on avait observé à 2h d’immersion lors d’une precedente etude. Donc le modele immersion seche est un modele pour etudier les transferts liquidiens en microgravité mais seulement en debut de phase d’immersion. Sur cette période de temps, les Brassarts de cuisse ont bien un effet protecteur pour les organes de la zone cephalique
Objective: to evaluate functional myocardial contractility after 21 days of head-down bed rest (HDTBR) in sedentary control (CON) or with a resistive vibration exercise (RVE) countermeasure (CM) applied, by using 4D echocardiographic (4D Echo) imaging and speckle tracking strain quantification.Methods: Twelve volunteers were enrolled in a crossover HDTBR design, and 4D Echo was performed in supine position (REST) at BDC-2 and at R+2, and in -6° HDTBR (on day 18), and also during the first and the last minute of the 80° head-up step of Standard Measures tilt test, performed at both BDC-2 and R+2. Radial (Rad-Str), longitudinal (Lg-Str) and twist (Tw-Str) strain were measured by 4D speckle tracking, as well as left ventricle diastolic volume (LVDV) and mass (LVmass).Results: On day 18: in the CON group, LVDV and LVmass were reduced (p<0.05), the Rad-Str decreased (p<0.05) and Tw-Str showed a tendency to increase (p< 0.11), with no changes in Lg-Str. In RVE group, LVDV and LV mass, as well as all the strain parameters remained unchanged.On R+2: in the CON group, LVDV and LVmass were not recovered in all subjects compared to pre-HDTBR (p<0.08), Rad-Str was still decreased (p<0.05), while Tw-Str tended to increase (p<0.09). These parameters remained unchanged in the RVE group.Tilt 80°: Rad-Str and Lg-Str values at 80° tilt were similar post HDT in both groups.Conclusion: 4D Echo and speckle tracking analysis showed that in the CON group, Rad-Str decreased concomitant with LVmass and LVDV with HDTBR, but this observation did not support the hypothesis that this HDTBR induced remodelling or a muscle atrophy. RVE acted to preserve both LVmass, LVDV and contractility during HDTBR, thus proving its effectiveness to this aim. Nevertheless, the significant HDTBR-induced changes observed in the CON group had only a limited effect on the cardiac contractile response as observed during post HDTBR tilt test. The level of contractility at 80° Tilt position was not affected neither by HDTBR nor by RVE CM.Purpose: The objective was to quantify the venous redistribution during a 4-day dry immersion (DI) and evaluate the effect of thigh cuffs.Methods: The study included 9 control (Co) and 9 subjects wearing thigh cuffs during daytime hours (CU). Ultrasound images were collected Pre DI, on the fourth day in the morning (D4 AM) and on the fourth day in the afternoon (D4 PM), to assess the following outcome variables: left ventricle dimension, stroke volume, and ejection fraction (LVD, SV, EF), jugular vein volume (JV), portal vein dimension (PV), middle cerebral vein velocity (MCVv). An additional measure of JV dimension was performed on the first day after having worn the cuffs for two hours (D1 2H).Results: The JV volume increased significantly from Pre to D1 2H in both groups, but increased more in the Co compare to the CU subjects (Co: 0,27+/0.15cm3 to 0.94+/-0;22 cm3;P<0.01 CU: 0,32+/-0.13 cm3 to 0.64+/-0.32 cm3 P<0.042).At D4 AM no difference was found between the two treatment groups for any of the parameters listed above.Stroke volume and EF decreased from Pre (SV:111+/-23cm3 to 93+/-24 cm3 p<0.05; EF:0.66+/-0.07 to 0.62+/-0.07 p<0.05). JV volume was slightly, but significantly increased (Co: 0.47+/-0.22cm3 CU:0.35+/-014cm3 P<0.05), while MCVv and PV remained unchanged from Pre DI. From D4 AM to PM these parameters did not show any significant change.Conclusion: The results confirm that DI induces, during the first 2-3 h, a significant cephalic fluid shift as observed in spaceflight. During this early phase the thigh cuffs reduced the amplitude of the fluid shift towards the head, but after 4 days in DI there was only a slight memory (residual) effect of DI on the jugular volume and no residual effect of thigh cuffs

碩士
國立成功大學
資訊工程學系碩博士班
96
The quantitative evaluation of muscular motion is an important index for rehabilitation biomechanics. For the clinical applications on 3D (2D+t) and 4D (3D+t) ultrasonic image sequences respectively, we propose two distinct multi-feature block-matching-based tracking methodologies to estimate muscular motion. The proposed multi-feature block matching methods in multilevel frame work achieve high accuracy and spatial adaptability through considering image intensity, motion velocity, neighbor relativity and selected features. By using multiple selected features, the discriminating region can be determined and provides a confident motion reference for homogeneous region tracking to overcome the motion ambiguity, which the traditional correlation coefficient measurement is extremely suffered from. In 3D motion tracking, the problem of region homogeneity can be handled by the proposed multi-feature block matching in multi-template framework combined with good discriminative neighbor reference and Kalman prediction. To quantify motion of borderless musculature from 4D image sequences, the end of fascia is chosen as target and tracked by multilevel multi-feature block matching with sectional adjustment and drift correction on a muscular motion model. The tolerance for image fuzziness and tissue deformation at low frame rate is effectively increased in the 4D estimation. In the experimental results, the accuracy in both methods is validated from in vivo musculoskeletal ultrasonic image sequences by comparing the results with the doctor-defined ground truth. This study can be applied to clinical diagnosis, such as sport injuries.

Accurate and frequent construction progress tracking provides critical input data for project systems such as cost and schedule control as well as billing. Unfortunately, conventional progress tracking is labor intensive, sometimes subject to negotiation, and often driven by arcane rules. Attempts to improve progress tracking have recently focused mainly on automation, using technologies such as 3D imaging, Global Positioning System (GPS), Ultra Wide Band (UWB) indoor locating, hand-held computers, voice recognition, wireless networks, and other technologies in various combinations. Three dimensional (3D) imaging technologies, such as 3D laser scanners (LADARs) and photogrammetry have shown great potential for saving time and cost for recording project 3D status and thus to support some categories of progress tracking. Although laser scanners in particular and 3D imaging in general are being investigated and used in multiple applications in the construction industry, their full potential has not yet been achieved. The reason may be that commercial software packages are still too complicated and time consuming for processing scanned data. Methods have however been developed for the automated, efficient and effective recognition of project 3D BIM objects in site laser scans. This thesis presents a novel system that combines 3D object recognition technology with schedule information into a combined 4D object based construction progress tracking system. The performance of the system is investigated on a comprehensive field database acquired during the construction of a steel reinforced concrete structure, Engineering V Building at the University of Waterloo. It demonstrates a degree of accuracy that meets or exceeds typical manual performance. However, the earned value tracking is the most commonly used method in the industry. That is why the object based automated progress tracking system is further explored, and combined with earned value theory into an earned value based automated progress tracking system. Nevertheless, both of these systems are focused on permanent structure objects only, not secondary or temporary. In the last part of the thesis, several approaches are proposed for concrete construction secondary and temporary object tracking. It is concluded that accurate tracking of structural building project progress is possible by combining a-priori 4D project models with 3D object recognition using the algorithms developed and presented in this thesis.

We present a fast and robust algorithm for lensless microscopy object 4D tracking called the DarkTrack. We validate the tracking accuracy on the simulated datasets and show the experimental results of tracking live spermatozoids.