105 research outputs found

    Development of a cognitive robotic system for simple surgical tasks

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    The introduction of robotic surgery within the operating rooms has significantly improved the quality of many surgical procedures. Recently, the research on medical robotic systems focused on increasing the level of autonomy in order to give them the possibility to carry out simple surgical actions autonomously. This paper reports on the development of technologies for introducing automation within the surgical workflow. The results have been obtained during the ongoing FP7 European funded project Intelligent Surgical Robotics (I-SUR). The main goal of the project is to demonstrate that autonomous robotic surgical systems can carry out simple surgical tasks effectively and without major intervention by surgeons. To fulfil this goal, we have developed innovative solutions (both in terms of technologies and algorithms) for the following aspects: fabrication of soft organ models starting from CT images, surgical planning and execution of movement of robot arms in contact with a deformable environment, designing a surgical interface minimizing the cognitive load of the surgeon supervising the actions, intra-operative sensing and reasoning to detect normal transitions and unexpected events. All these technologies have been integrated using a component-based software architecture to control a novel robot designed to perform the surgical actions under study. In this work we provide an overview of our system and report on preliminary results of the automatic execution of needle insertion for the cryoablation of kidney tumours

    Segmentierung medizinischer Bilddaten und bildgestützte intraoperative Navigation

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    Die Entwicklung von Algorithmen zur automatischen oder semi-automatischen Verarbeitung von medizinischen Bilddaten hat in den letzten Jahren mehr und mehr an Bedeutung gewonnen. Das liegt zum einen an den immer besser werdenden medizinischen Aufnahmemodalitäten, die den menschlichen Körper immer feiner virtuell abbilden können. Zum anderen liegt dies an der verbesserten Computerhardware, die eine algorithmische Verarbeitung der teilweise im Gigabyte-Bereich liegenden Datenmengen in einer vernünftigen Zeit erlaubt. Das Ziel dieser Habilitationsschrift ist die Entwicklung und Evaluation von Algorithmen für die medizinische Bildverarbeitung. Insgesamt besteht die Habilitationsschrift aus einer Reihe von Publikationen, die in drei übergreifende Themenbereiche gegliedert sind: -Segmentierung medizinischer Bilddaten anhand von vorlagenbasierten Algorithmen -Experimentelle Evaluation quelloffener Segmentierungsmethoden unter medizinischen Einsatzbedingungen -Navigation zur Unterstützung intraoperativer Therapien Im Bereich Segmentierung medizinischer Bilddaten anhand von vorlagenbasierten Algorithmen wurden verschiedene graphbasierte Algorithmen in 2D und 3D entwickelt, die einen gerichteten Graphen mittels einer Vorlage aufbauen. Dazu gehört die Bildung eines Algorithmus zur Segmentierung von Wirbeln in 2D und 3D. In 2D wird eine rechteckige und in 3D eine würfelförmige Vorlage genutzt, um den Graphen aufzubauen und das Segmentierungsergebnis zu berechnen. Außerdem wird eine graphbasierte Segmentierung von Prostatadrüsen durch eine Kugelvorlage zur automatischen Bestimmung der Grenzen zwischen Prostatadrüsen und umliegenden Organen vorgestellt. Auf den vorlagenbasierten Algorithmen aufbauend, wurde ein interaktiver Segmentierungsalgorithmus, der einem Benutzer in Echtzeit das Segmentierungsergebnis anzeigt, konzipiert und implementiert. Der Algorithmus nutzt zur Segmentierung die verschiedenen Vorlagen, benötigt allerdings nur einen Saatpunkt des Benutzers. In einem weiteren Ansatz kann der Benutzer die Segmentierung interaktiv durch zusätzliche Saatpunkte verfeinern. Dadurch wird es möglich, eine semi-automatische Segmentierung auch in schwierigen Fällen zu einem zufriedenstellenden Ergebnis zu führen. Im Bereich Evaluation quelloffener Segmentierungsmethoden unter medizinischen Einsatzbedingungen wurden verschiedene frei verfügbare Segmentierungsalgorithmen anhand von Patientendaten aus der klinischen Routine getestet. Dazu gehörte die Evaluierung der semi-automatischen Segmentierung von Hirntumoren, zum Beispiel Hypophysenadenomen und Glioblastomen, mit der frei verfügbaren Open Source-Plattform 3D Slicer. Dadurch konnte gezeigt werden, wie eine rein manuelle Schicht-für-Schicht-Vermessung des Tumorvolumens in der Praxis unterstützt und beschleunigt werden kann. Weiterhin wurde die Segmentierung von Sprachbahnen in medizinischen Aufnahmen von Hirntumorpatienten auf verschiedenen Plattformen evaluiert. Im Bereich Navigation zur Unterstützung intraoperativer Therapien wurden Softwaremodule zum Begleiten von intra-operativen Eingriffen in verschiedenen Phasen einer Behandlung (Therapieplanung, Durchführung, Kontrolle) entwickelt. Dazu gehört die erstmalige Integration des OpenIGTLink-Netzwerkprotokolls in die medizinische Prototyping-Plattform MeVisLab, die anhand eines NDI-Navigationssystems evaluiert wurde. Außerdem wurde hier ebenfalls zum ersten Mal die Konzeption und Implementierung eines medizinischen Software-Prototypen zur Unterstützung der intraoperativen gynäkologischen Brachytherapie vorgestellt. Der Software-Prototyp enthielt auch ein Modul zur erweiterten Visualisierung bei der MR-gestützten interstitiellen gynäkologischen Brachytherapie, welches unter anderem die Registrierung eines gynäkologischen Brachytherapie-Instruments in einen intraoperativen Datensatz einer Patientin ermöglichte. Die einzelnen Module führten zur Vorstellung eines umfassenden bildgestützten Systems für die gynäkologische Brachytherapie in einem multimodalen Operationssaal. Dieses System deckt die prä-, intra- und postoperative Behandlungsphase bei einer interstitiellen gynäkologischen Brachytherapie ab

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    [ES] El aumento de los procedimientos usando la robótica quirúrgica en la última década demanda un alto número de cirujanos, capaces de teleoperar sistemas avanzados y complejos y, al mismo tiempo, de aprovechar los beneficios de la Cirugía Asistida por Robot de forma segura y efectiva. En la actualidad, los planes de formación se basan en la Realidad Virtual y entornos simulados para lograr un establecimiento escalable, rentable y completo del conjunto de habilidades quirúrgicas robóticas. Este trabajo se centra en el desarrolloo de un una escenario clínico mediante sensores que asistan al ciruajano durante su entrenamiento con el daVinci®, implementados en un entorno físico impreso en 3D. Esta investigación busca la obtención de un modelo segmentado, la impresión 3D del modelo para simular el escenraio clínico real y así abituar al cirujano a la interacción de los órganos y tejidos con el robot; y la implementación de sensores con que asistir al cirjuano en el entrenamiento. Para ello, con el fin de demostrar la eficacia de la asistencia durante los entrenamientos, así como la validez de los ejercicios de la operación simulada se ha realizado un estudio con doce voluntarios.Tanto la asistencia visual como el uso de fantomas 3D muestran ser una alternativa óptima para el aprendizaje de la habilidades requeridas en la cirugía robótica: manifestandose un paso adelante hacia un entrenamiento personlizado para cada cirujano.[EN] The increase of surgical procedures using robotic technology in the last decade demands a high number of surgeons capable of teleoperating advanced and complex systems while safely and effectively taking advantage of Robot-Assisted Surgery benefits. Currently, training plans rely on Virtual Reality and simulated environments to achieve a scalable, cost-effective, and comprehensive establishment of robotic surgical skills. This work focuses on the development of a clinical scenario through sensors that assist the surgeon during their training with the daVinci® system, implemented in a 3D-printed physical environment. This research aims to obtain a segmented model, 3D printing the model to simulate the real clinical scenario, thus familiarizing the surgeon with the interaction of organs and tissues with the robot. Additionally, sensors are implemented to assist the surgeon during training. Therefore, to demonstrate the effectiveness of the assistance during the training sessions and the validity of the exercises in the simulated operation, a study was conducted with twelve volunteers. Both visual assistance and the use of 3D phantoms prove to be an optimal alternative for learning the required skills in robotic surgery, representing a significant step forward towards personalized training for each surgeon.Castillo Rosique, P. (2023). Development sensorized 3D-printed realistic phantom to scale for surgical training with a daVinci robot. Universitat Politècnica de València. http://hdl.handle.net/10251/19804

    4D imaging of heart vaso-architecture after myocardial infarction

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    Cardiovascular diseases remain the number one cause of death globally. There is an ongoing desire to study the distribution and structural changes of the vaso-architecture in the diseased heart in cardiovascular research groups all over the world. The ability to acquire high resolution 3D-images of the heart vasculature enables to study heart diseases more in detail and eventually obtain interesting new findings and new treatments. In this work, we introduce a pipeline for high resolution 3D-imaging of the changes in mouse heart vasculature after a myocardial infarction is produced with Single Plane Illumination Microscopy (SPIM). To achieve high resolution 3D-images, protocols for optical tissue clearing (CUBIC tissue clearing technique) were combined with vasculature labelling methods (IHC and intravenous perfused lectin), enabling the visualization for the very first time of the whole heart vasculature. We here also describe the methods used for image pre-processing of the acquired data, mainly for correction of SPIM-image artifacts and for segmentation of the structures of interest. Finally, the analysis of the changes in vasculature between healthy hearts with the different stages of chronic myocardial infarction (7, 14 and 28 days post-infarction) will provide us a tool to know how this disease affects not only to infarcted region but to the whole heart volume.Ingeniería Biomédic

    Development and Evaluation of Modeling Approaches for Extrusion-based Additive Manufacturing of Thermoplastics

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    This work focuses on evaluating different modeling approaches and model parameters for thermoplastic AM, with the goal of informing more efficient and effective modeling approaches. First, different modeling approaches were tested and compared to experiments. From this it was found that all three of the modeling approaches provide comparable results and provide similar results to experiments. Then one of the modeling approaches was tested on large scale geometries, and it was found that the model results matched experiments closely. Then the effect of different material properties was evaluated, this was done by performing a fractional factorial design of experiments where the factors were ±15% of the baseline material properties. From this it was found that coefficient of thermal expansion (CTE) is by far the most important material property for the simulated warpage. This test was repeated with a simulated desktop printer, simulated commercial printer and a simulated room scaled printer to evaluate if the relevant material properties change as a function of length scale; it was found that as length scale increases, conduction becomes increasingly important, but this effect was still small compared to that of CTE. Finally, the effect of the environment was evaluated by running a Latin hypercube Design of Experiments (DOE) over environmental factors; it was found that the most important effects are the bed and enclosure temperatures. It also pointed to the feasibility of using radiative heating to mitigate warpage, because as length scale increases natural convection becomes less important. This work is significant because it leverages modeling and simulation to evaluate the effects of the different phenomena in 3D printing and points out some of the gaps in the current state of the art that are not evident from performing simple experiments or simple simulations, namely implementing a model for build plate adhesion

    Machine Learning/Deep Learning in Medical Image Processing

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    Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, “Machine Learning/Deep Learning in Medical Image Processing”, has been launched to provide an opportunity for researchers in the area of medical image processing to highlight recent developments made in their fields with ML/DL. Seven excellent papers that cover a wide variety of medical/clinical aspects are selected in this special issue

    Cost-Efficient Low-Volume Production Through Additive Manufacturing

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    Master's thesis in Industrial economicsAdditive manufacturing, commonly known as 3D Printing, is a production method of rising popularity. The method works by adding layers of material, in contrast to subtracting, which is the dominating method today. The objective of this thesis has been to evaluate the cost-efficiency of producing relatively complex parts through additive manufacturing, compared to subtractive methods with production volumes less than 20 units. Initial findings narrow the additive methods down from seven, to two methods (Selective Laser Sintering/Melting and Fused Filament Fabrication) which are found best fit for end use parts. Data is gathered by acquiring price quotes from manufacturing companies for two plastic and two aluminium parts, through subtractive and additive methods. In order to look for intersections found at intermediate production volumes, the companies were asked to give price for 1, 5 and 20 units of the same item. Compared to subtractive methods, additive manufacturing processes are found to exhibit less cost-decrease per additional unit produced. The cost of producing a 150gram plastic part through the additive process was found to be between a quarter, and half the cost of the subtractive machining processes. In comparison, for a 15 gram part, additive manufacturing was found to be even more cost-efficient, with prices ranging between 10% and 20% of the alternative. The metal additive manufacturing process was found to be 15% cheaper than the subtractive at producing one single small part (100gram), whereas in contrast, it was 50% more expensive when producing 20 units. For manufacturing larger parts (500gram), it was found to be between 75 and 150% more expensive than the subtractive machining. As such this thesis complements existing literature on when to choose an additive process over the subtractive, and shows that whilst plastic additive processes are very cost-efficient for low volumes, metal additive manufacturing still has a way to go before becoming the natural choice for low-volume productio

    Optimization of computer-assisted intraoperative guidance for complex oncological procedures

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    Mención Internacional en el título de doctorThe role of technology inside the operating room is constantly increasing, allowing surgical procedures previously considered impossible or too risky due to their complexity or limited access. These reliable tools have improved surgical efficiency and safety. Cancer treatment is one of the surgical specialties that has benefited most from these techniques due to its high incidence and the accuracy required for tumor resections with conservative approaches and clear margins. However, in many cases, introducing these technologies into surgical scenarios is expensive and entails complex setups that are obtrusive, invasive, and increase the operative time. In this thesis, we proposed convenient, accessible, reliable, and non-invasive solutions for two highly complex regions for tumor resection surgeries: pelvis and head and neck. We explored how the introduction of 3D printing, surgical navigation, and augmented reality in these scenarios provided high intraoperative precision. First, we presented a less invasive setup for osteotomy guidance in pelvic tumor resections based on small patient-specific instruments (PSIs) fabricated with a desktop 3D printer at a low cost. We evaluated their accuracy in a cadaveric study, following a realistic workflow, and obtained similar results to previous studies with more invasive setups. We also identified the ilium as the region more prone to errors. Then, we proposed surgical navigation using these small PSIs for image-to-patient registration. Artificial landmarks included in the PSIs substitute the anatomical landmarks and the bone surface commonly used for this step, which require additional bone exposure and is, therefore, more invasive. We also presented an alternative and more convenient installation of the dynamic reference frame used to track the patient movements in surgical navigation. The reference frame is inserted in a socket included in the PSIs and can be attached and detached without losing precision and simplifying the installation. We validated the setup in a cadaveric study, evaluating the accuracy and finding the optimal PSI configuration in the three most common scenarios for pelvic tumor resection. The results demonstrated high accuracy, where the main source of error was again incorrect placements of PSIs in regular and homogeneous regions such as the ilium. The main limitation of PSIs is the guidance error resulting from incorrect placements. To overcome this issue, we proposed augmented reality as a tool to guide PSI installation in the patient’s bone. We developed an application for smartphones and HoloLens 2 that displays the correct position intraoperatively. We measured the placement errors in a conventional and a realistic phantom, including a silicone layer to simulate tissue. The results demonstrated a significant reduction of errors with augmented reality compared to freehand placement, ensuring an installation of the PSI close to the target area. Finally, we proposed three setups for surgical navigation in palate tumor resections, using optical trackers and augmented reality. The tracking tools for the patient and surgical instruments were fabricated with low-cost desktop 3D printers and designed to provide less invasive setups compared to previous solutions. All setups presented similar results with high accuracy when tested in a 3D-printed patient-specific phantom. They were then validated in the real surgical case, and one of the solutions was applied for intraoperative guidance. Postoperative results demonstrated high navigation accuracy, obtaining optimal surgical outcomes. The proposed solution enabled a conservative surgical approach with a less invasive navigation setup. To conclude, in this thesis we have proposed new setups for intraoperative navigation in two complex surgical scenarios for tumor resection. We analyzed their navigation precision, defining the optimal configurations to ensure accuracy. With this, we have demonstrated that computer-assisted surgery techniques can be integrated into the surgical workflow with accessible and non-invasive setups. These results are a step further towards optimizing the procedures and continue improving surgical outcomes in complex surgical scenarios.Programa de Doctorado en Ciencia y Tecnología Biomédica por la Universidad Carlos III de MadridPresidente: Raúl San José Estépar.- Secretario: Alba González Álvarez.- Vocal: Simon Droui

    Nonlinear effects in finite elements analysis of colorectal surgical clamping

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    Minimal Invasive Surgery (MIS) is a procedure that has increased its applications in past few years in different types of surgeries. As number of application fields are increasing day by day, new issues have been arising. In particular, instruments must be inserted through a trocar to access the abdominal cavity without capability of direct manipulation of tissues, so a loss of sensitivity occurs. Generally speaking, the student of medicine or junior surgeons need a lot of practice hours before starting any surgical procedure, since they have to difficulty in acquiring specific skills (hand–eye coordination among others) for this type of surgery. Here is what the surgical simulator present a promising training method using an approach based on Finite Element Method (FEM). The use of continuum mechanics, especially Finite Element Analysis (FEA) has gained an extensive application in medical field in order to simulate soft tissues. In particular, colorectal simulations can be used to understand the interaction between colon and the surrounding tissues and also between colon and instruments. Although several works have been introduced considering small displacements, FEA applied to colorectal surgical procedures with large displacements is a topic that asks for more investigations. This work aims to investigate how FEA can describe non-linear effects induced by material properties and different approximating geometries, focusing as test-case application colorectal surgery. More in detail, it shows a comparison between simulations that are performed using both linear and hyperelastic models. These different mechanical behaviours are applied on different geometrical models (planar, cylindrical, 3D-SS and a real model from digital acquisitions 3D-S) with the aim of evaluating the effects of geometric non-linearity. Final aim of the research is to provide a preliminary contribution to the simulation of the interaction between surgical instrument and colon tissues with multi-purpose FEA in order to help the preliminary set-up of different bioengineering tasks like force-contact evaluation or approximated modelling for virtual reality (surgical simulations). In particular, the contribution of this work is focused on the sensitivity analysis of the nonlinearities by FEA in the tissue-tool interaction through an explicit FEA solver. By doing in this way, we aim to demonstrate that the set-up of FEA computational surgical tools may be simplified in order to provide assistance to non-expert FEA engineers or medicians in more precise way of using FEA tools
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