Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models

A semi-automatic segmentation algorithm for abdominal aortic aneurysms (AAA), and based on Active Shape Models (ASM) and texture models, is presented in this work. The texture information is provided by a set of four 3D magnetic resonance (MR) images, composed of axial slices of the abdomen, where lumen, wall and intraluminal thrombus (ILT) are visible. Due to the reduced number of images in the MRI training set, an ASM and a custom texture model based on border intensity statistics are constructed. For the same reason the shape is characterized from 35-computed tomography angiography (CTA) images set so the shape variations are better represented. For the evaluation, leave-one-out experiments have been held over the four MRI set.

Motion correction algorithm of lung tumors for respiratory gated PET images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

Motion Correction Algorithm of Lung Tumors for Respiratory Gated PET Images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation

Robot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury) -- The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement -- The economical prevalent method to estimate the patient posture in Exoskeleton-based RAR is to approximate the limb joint angles with the ones of the Exoskeleton -- This approximation is rough since their kinematic structures differ -- Motion capture systems (MOCAPs) can improve the estimations, at the expenses of a considerable overload of the therapy setup -- Alternatively, the Extended Inverse Kinematics Posture Estimation (EIKPE) computational method models the limb and Exoskeleton as differing parallel kinematic chains -- EIKPE has been tested with single DOFmovements of the wrist and elbow joints -- This paper presents the assessment of EIKPEwith elbow-shoulder compoundmovements (i.e., object prehension) -- Ground-truth for estimation assessment is obtained from an optical MOCAP (not intended for the treatment stage) -- The assessment shows EIKPE rendering a good numerical approximation of the actual posture during the compoundmovement execution, especially for the shoulder joint angles -- This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types --

Integrated high pressure microhydraulic actuation and control for surgical instruments

To reduce the surgical trauma to the patient, minimally invasive surgery is gaining considerable importance since the eighties. More recently, robot assisted minimally invasive surgery was introduced to enhance the surgeon's performance in these procedures. This resulted in an intensive research on the design, fabrication and control of surgical robots over the last decades. A new development in the field of surgical tool manipulators is presented in this article: a flexible manipulator with distributed degrees of freedom powered by microhydraulic actuators. The tool consists of successive flexible segments, each with two bending degrees of freedom. To actuate these compliant segments, dedicated fluidic actuators are incorporated, together with compact hydraulic valves which control the actuator motion. Especially the development of microvalves for this application was challenging, and are the main focus of this paper. The valves distribute the hydraulic power from one common high pressure supply to a series of artificial muscle actuators. Tests show that the angular stroke of the each segment of this medical instrument is 90°. © 2012 Springer Science+Business Media, LLC.

五轴磨抛机器人补偿算法研究与实现

通过分析基于模型的补偿方法和非模型补偿方法的优缺点,结合一个五轴磨抛机器人的结构特点,提出了两种补偿方法相结合的混合补偿算法.针对平移关节误差的主要来源难于建模的特点,采用非模型的方法进行补偿;针对转动关节误差主要来源为几何参数误差,能够建模,但有些参数随机器人末端位置不同而变化的特点,采用二者相结合的混合方法进行补偿.通过对该机器人系统的实验,验证了方法的有效性和可行性.

Implementation of robotic laparoscopic cholecystectomy in a university hospital.

BACKGROUND: Robot surgery is a further step towards new potential developments in minimally invasive surgery. Surgeons must keep abreast of these new technologies and learn their limits and possibilities. Robot-assisted laparoscopic cholecystectomy has not yet been performed in our institution. The purpose of this report is to present the pathway of implementation of robotic laparoscopic cholecystectomy in a university hospital. METHODS: The Zeus(R) robot system was used. Experimental training was performed on animals. The results of our experimental training allowed us to perform our first two clinical cases. RESULTS: Robot arm set-up and trocar placement required 53 and 35 minutes. Operative time were 59 and 45 minutes respectively. The overall operative time was 112 and 80 minutes, respectively. There were no intraoperative complications. Patients were discharged from the hospital after an overnight stay. CONCLUSION: Robotic laparoscopic cholecystectomy is safe and patient recovery similar to those of standard laparoscopy. At present, there are no advantages of robotic over conventional surgery. Nevertheless, robots have the potential to revolutionise the way surgery is performed. Robot surgery is not reserved for a happy few. This technology deserves more attention because it has the potential to change the way surgery is performed.

Fast Object Recognition in Noisy Images Using Simulated Annealing

A fast simulated annealing algorithm is developed for automatic object recognition. The normalized correlation coefficient is used as a measure of the match between a hypothesized object and an image. Templates are generated on-line during the search by transforming model images. Simulated annealing reduces the search time by orders of magnitude with respect to an exhaustive search. The algorithm is applied to the problem of how landmarks, for example, traffic signs, can be recognized by an autonomous vehicle or a navigating robot. The algorithm works well in noisy, real-world images of complicated scenes for model images with high information content.

Ejercicio y resultados clínicos en pacientes con enfermedad de Parkinson: una revisión sistemática y metaanálisis

Antecedentes. La enfermedad de Parkinson (EP) es la segunda enfermedad neurodegenerativa más común en el mundo, la cual afecta el componente físico, psicológico y social de los individuos que la padecen. Numerosos estudios han abordado los beneficios de diferentes programas de ejercicio, llegando a ser una estrategia no-farmacológica efectiva para aminorar el deterioro funcional de los pacientes con EP. Objetivo. Determinar los efectos de las diferentes modalidades de ejercicio físico en los principales desenlaces clínicos en pacientes con EP. Métodos. Se consultaron las bases de datos MEDLINE, EMBASE, Scopus, CENTRAL y PEDro desde febrero de 1990 hasta febrero de 2014 para identificar Ensayos Clínicos Aleatorizados (ECA) publicados. Además, se examinaron las listas de referencias de otras revisiones y de estudios identificados. La extracción de datos se realizó por dos autores independientes. Se empleó un modelo de efectos aleatorios en presencia de heterogeneidad estadística (I2>50%). El sesgo de publicación fue evaluado mediante el gráfico de embudo. Resultados: Un total de 18 estudios fueron incluidos. Se encontraron diferencias estadísticamente significativas en las intervenciones con ejercicio y las siguientes medidas de resultado, severidad de los síntomas motores (MDS-UPDRS) DME 1.44, IC 95% [-2.09 a -0.78] (p<0.001) I2= 87,9% y el equilibrio DME 0,52 IC 95% [0,30 a 0,74] (p<0.001) I2= 85,6%. En el análisis de subgrupos en la modalidad de ejercicio aeróbico, en MDS-UPDRS DME -1,28, IC 95% [-1,98 a -0,59] (p<0.001), 3 calidad de vida DME -1,91 IC 95% [-2,76 a -1,07] (p<0.001), equilibrio DME 0,54 IC 95% [0,31 a 0,77] (p<0.001), 10-m WT DME 0,15 IC 95% [0,06 a 0,25] (p<0.001) y Vo2 máximo DME -1,09 IC 95% [-1,31 a -0,88] (p=0.001), 6MWT DME 40,46 IC 95% [11,28 a 69,65] (p=0.007). Conclusiones: El ejercicio aeróbico produjo mejoras significativas en MDS UPDRS, equilibrio, calidad de vida, 10-m WT y y Vo2 máximo; mientras que el ejercicio combinado mejoró la fuerza.

Reach & grasp therapy: Design and control of a 9-DOF robotic neuro-rehabilitation system

This paper presents the Gentle/G integrated system for reach & grasp therapy retraining following brain injury. The design, control and integration of an experimental grasp assistance unit is described for use in robot assisted stroke rehabilitation. The grasp assist unit is intended to work with the hardware and software of the Gentle/S robot although the hardware could be adapted to other rehabilitation applications. When used with the Gentle/S robot a total of 6 active and 3 passive degrees of freedom are available to provide active, active assist or passive grasp retraining in combination with reaching movements in a reach-grasp-transfer-release sequence.

Synthesis of Hand Exoskeletons for the Rehabilitation of Post-Stroke Patients

This dissertation presents the synthesis of a hand exoskeleton (HE) for the rehabilitation of post-stroke patients. Through the analysis of state-of-the-art, a topological classification was proposed. Based on the proposed classification principles, the rehabilitation HEs were systematically analyzed and classified. This classification is helpful to both understand the reason of proposing certain solutions for specific applications and provide some useful guidelines for the design of a new HE, that was actually the primary motivation of this study. Further to this classification, a novel rehabilitation HE was designed to support patients in cylindrical shape grasping tasks with the aim of recovering the basic functions of manipulation. The proposed device comprises five planar mechanisms, one per finger, globally actuated by two electric motors. Indeed, the thumb flexion/extension movement is controlled by one actuator whereas a second actuator is devoted to the control of the flexion/extension of the other four fingers. By focusing on the single finger mechanism, intended as the basic model of the targeted HE, the feasibility study of three different 1 DOF mechanisms are analyzed: a 6-link mechanism, that is connected to the human finger only at its tip, an 8-link and a 12-link mechanisms where phalanges and articulations are part of the kinematic chain. The advantages and drawbacks of each mechanism are deeply analyzed with respect to targeted requirements: the 12-link mechanism was selected as the most suitable solution. The dimensional synthesis based on the Burmester theory as well as kinematic and static analyses were separately done for all fingers in order to satisfy the desired specifications. The HE was finally designed and a prototype was built. The experimental results of the first tests are promising and demonstrate the potential for clinical applications of the proposed device in robot-assisted training of the human hand for grasping functions.