438 research outputs found

    Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

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    Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

    Patient-specific modelling in orthopedics: from image to surgery

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    In orthopedic surgery, to decide upon intervention and how it can be optimized, surgeons usually rely on subjective analysis of medical images of the patient, obtained from computed tomography, magnetic resonance imaging, ultrasound or other techniques. Recent advancements in computational performance, image analysis and in silico modeling techniques have started to revolutionize clinical practice through the development of quantitative tools, including patient#specific models aiming at improving clinical diagnosis and surgical treatment. Anatomical and surgical landmarks as well as features extraction can be automated allowing for the creation of general or patient-specific models based on statistical shape models. Preoperative virtual planning and rapid prototyping tools allow the implementation of customized surgical solutions in real clinical environments. In the present chapter we discuss the applications of some of these techniques in orthopedics and present new computer-aided tools that can take us from image analysis to customized surgical treatment

    MedEdit : a computer assisted image processing and navigation system for orthopedic trauma surgery

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    The surgery of fractured bones is often a very complex problem. That is the reason why it would be beneficial to create a geometric and mechanic model of the bones before surgical intervention. The model geometry is based on the CT images of the patient and the known physical properties of the bone. A computerised system is presented here, called MedEdit, which helps a surgeon plan an operation. The system includes a Finite Element Analysis (FEA) program to measure the stress effects of the possible surgical solutions. Following the simulation and analysis of the behaviour of the modelled bone, surgeons can find the best surgical solution for the patient

    Radiomics in Medical Imaging with Application to Surgical Innovation

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    Modern surgery today has greatly improved healthcare due to technological advancements in medical imaging. It has fostered a culture of innovation that has progressed with continuous and incremental changes towards curing patients’ ailments. With evidence-based assessments gaining prominence in modern surgery, Radiomics has become crucial to resolving problems through the integration of the best scientific data with the correct clinical expertise. As a quantitative approach to medical imaging, Radiomics uses mathematical analysis to improve the data made available to clinicians, which greatly influences their decision-making ability. In this thesis, we focus on two applications: pelvic bone segmentation from CT data for designing patient-specific customizable pessaries; and quantitative assessment of breast morphology, for reconstructive breast surgeries. For pelvic bone segmentation, we investigate several encoder-decoder network configurations trained on limited data and use histogram based features from Radiomics to take a data-centric view towards the problem and boost the model performance on completely unseen data through histogram specification. Then we evaluate the performance on two publicly available CT datasets. For assessment of breast morphology, we propose a novel metric for quantifying the overall dissimilarity between two breast mounds, called VIMA, by using shape and size based features from iso-contours. The methodology was experimented on 3D scans of artificial breasts and found to be highly useful in an intra-operative setting for aiding surgeons during aesthetic breast surgeries

    Three Dimensional Nonlinear Statistical Modeling Framework for Morphological Analysis

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    This dissertation describes a novel three-dimensional (3D) morphometric analysis framework for building statistical shape models and identifying shape differences between populations. This research generalizes the use of anatomical atlases on more complex anatomy as in case of irregular, flat bones, and bones with deformity and irregular bone growth. The foundations for this framework are: 1) Anatomical atlases which allow the creation of homologues anatomical models across populations; 2) Statistical representation for output models in a compact form to capture both local and global shape variation across populations; 3) Shape Analysis using automated 3D landmarking and surface matching. The proposed framework has various applications in clinical, forensic and physical anthropology fields. Extensive research has been published in peer-reviewed image processing, forensic anthropology, physical anthropology, biomedical engineering, and clinical orthopedics conferences and journals. The forthcoming discussion of existing methods for morphometric analysis, including manual and semi-automatic methods, addresses the need for automation of morphometric analysis and statistical atlases. Explanations of these existing methods for the construction of statistical shape models, including benefits and limitations of each method, provide evidence of the necessity for such a novel algorithm. A novel approach was taken to achieve accurate point correspondence in case of irregular and deformed anatomy. This was achieved using a scale space approach to detect prominent scale invariant features. These features were then matched and registered using a novel multi-scale method, utilizing both coordinate data as well as shape descriptors, followed by an overall surface deformation using a new constrained free-form deformation. Applications of output statistical atlases are discussed, including forensic applications for the skull sexing, as well as physical anthropology applications, such as asymmetry in clavicles. Clinical applications in pelvis reconstruction and studying of lumbar kinematics and studying thickness of bone and soft tissue are also discussed

    A total hip replacement toolbox : from CT-scan to patient-specific FE analysis

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    The feasibility of using feature-flow and label transfer system to segment medical images with deformed anatomy in orthopedic surgery

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    In computer-aided surgical systems, to obtain high fidelity three-dimensional models, we require accurate segmentation of medical images. State-of-art medical image segmentation methods have been used successfully in particular applications, but they have not been demonstrated to work well over a wide range of deformities. For this purpose, I studied and evaluated medical image segmentation using the feature-flow based Label Transfer System described by Liu and colleagues. This system has produced promising results in parsing images of natural scenes. Its ability to deal with variations in shapes of objects is desirable. In this paper, we altered this system and assessed its feasibility of automatic segmentation. Experiments showed that this system achieved better recognition rates than those in natural-scene parsing applications, but the high recognition rates were not consistent across different images. Although this system is not considered clinically practical, we may improve it and incorporate it with other medical segmentation tools

    Image Guidance in Telemanipulator Assisted Urology Surgery

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    This thesis outlines the development of an image guided surgery system, intended for use in \davinci assisted radical prostatectomy but more generally applicable to laparoscopic urology surgery. We defined the key performance parameter of the system as the accuracy of overlaying modelled anatomy onto the surgical scene. This thesis is primarily concerned with determining the system accuracy based on an analysis of the system's components. A common error measure was defined for all system components. This is an on screen error (measured in pixels) based on the error in projecting a single point lying near the apex of the prostate with the endoscope in a typical surgical pose. In this case the projected point was approximately 200 mm from the endoscope lens. An intraoperative coordinate system is first defined as the coordinate system of an optical tracking system used to track the endoscope. The MRI image of the patient is transformed into the intraoperative coordinate system. Prior to surgery the endoscope is calibrated and during surgery the endoscope is tracked, defining a transform from the coordinates of the optical tracking system to the endoscope screen. This transform is used to project the MRI image onto the endoscope video display. The early part of the thesis describes a novel algorithm for registering MRI to ultrasound images of the bone which was used to put the MRI image into the intraoperative coordinate system. Using this algorithm avoids the need for fiducial markers. The table below shows the errors (as on screen pixel RMS) due to using this algorithm. An approximate value as RMS distance error at the prostate apex point is also included

    Computer assisted surgery for fracture reduction and deformity correction of the pelvis and long bones

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    Many orthopaedic operations, for example osteotomies, are not preoperative planned. The operation result depends on the experience of the operating surgeon. In the industry new developments are not longer curried out without CAD planning or computer simulations. Only in medicine the operation technology of corrective osteotomies are still in their infant stage in the last 30 years. Two dimensional analysis is not accurate that results in operation errors in the operating room. The surgeon usually obtains the preoperative information about the current bone state by radiographs. In case of complex operations (also inserting implants) planning is required. Planning based on radiographs has some system-dependent disadvantages like small accuracy, requirement of time for corrections ( distortions due to the projection) and restrictions, if complex corrections are necessary. Today the computer tomography is used as a solution. It is the only modality that allows to reach the accuracy and the resolution required for a good 3D-planning. However its a high dose rate for the patient is the serious disadvantage. Therefore in dilemma between the low dose rate and an adequate planning the first is often preferred. However in future it is expected that good operation results are guarantied only with implementation of 3D-planung. MR systems provide image information too, from which indirectly bones can be extracted. But due to their large distortions (susceptibility, non non-homogeneity of magnetic field), small spatial dissolution and the high costs, it is not expected that MRI represents an alternative in next time. The solution is the use of other image modalities. Ultrasound is here a good compromise both of the costs of the accuracy. In this work I developed an algorithm, which can produce 3D bone models from ultrasonic data. They have good resolution and accuracy compared with CT, and therefore can be used for 3D planning. In the work an improved procedure for segmenting bone surfaces is realised in combination with methods for the fusion for a three-dimensional model. The novelty of the presented work is in new approaches to realising an operation planning system, based on 3D computations, and implementing the intraoperative control by a guided ultrasound system for bone tracking. To realise these ideas the following tasks are solved: - bone modelling from CT data; - real-time extraction of bone surfaces from ultrasound imaging; - tracking the bone with respect to CT bone model. - integrating and implementing the above results in the development of an operation planning system for osteotomy corrections that supports on-line measurements, different types of deformity correction, a bone geometry design and a high level of automation. The developed osteotomy planning system allows to investigate the pathology, makes its analysis, finds an optimal way to realise surgery and provides visual and quantitative information about the results of the virtual operation. Therefore, the implementation of the proposed system can be considered as an additional significant tool for the diagnosis and orthopaedic surgery. The major parts of the planning system are: bone modelling from 3D data derived from CT, MRI or other modalities, visualisation of the elements of the 3D scene in real-time, and the geometric design of bone elements. A high level of automation allows the surgeon to reduce significantly the time of the operation plane development
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