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检索条件"任意字段=Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions and Modeling"

共 966 条记录，以下是241-250 订阅

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Enabling low-cost point-of-care ultrasound imaging system using single element transducer and delta configuration actuator

Enabling low-cost point-of-care ultrasound imaging system us...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Xu, Keshuai Kim, Younsu Boctor, Emad M. Zhang, Haichong K. Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA Johns Hopkins Univ Lab Computat Sensing & Robot Baltimore MD 21218 USA Johns Hopkins Univ Dept Radiol Baltimore MD USA Worcester Polytech Inst Dept Biomed Engn Worcester MA 01609 USA Worcester Polytech Inst Robot Engn Worcester MA 01609 USA

ISBN: (纸本)9781510625501

Ultrasound is a space-effective and real-time modality for image-guided intervention for challenging and complication prone procedure. Yet, conventional diagnostic ultrasound machines usually require the use of expensive probes and bulky electronics because of the need to acquire and process hundreds of channel data. In contrast, a single element ultrasound system creates a virtual array by scanning an ultrasound element with robotic actuation and tracking instead of using a physical array of ultrasound elements as in the conventional ultrasound machine. It not only enables visualization of procedures that otherwise require a custom probe but also dramatically reduces cost and improves the accessibility of image-guided intervention in point-of-care applications. In this work, we present a single-element ultrasound imaging system with a delta configuration actuator modified from a low-cost commercial off-the-shelf 3-D printer, which can serve as both a prototype for clinical application and a research platform. We evaluated the image quality with a needle-based ultrasound system by imaging glass wire and spine phantoms. The results indicate the feasibility of compact and economically friendly single-element ultrasound imaging solution for applications including spinal intervention such as guiding lumbar puncture and epidural needle insertion.

关键词： Ultrasonography Printing 3D printing Actuators image quality 3D image processing imaging systems Transducers

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Multimodal image registration of pre- and intra-interventional data for surgical planning of transarterial chemoembolisation

Multimodal image registration of pre- and intra-intervention...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Waldkirch, Barbara Engelhardt, Sandy Zoellner, Frank G. Schad, Lothar R. Wolf, Ivo Mannheim Univ Appl Sci Inst Med Informat Mannheim Germany Heidelberg Univ Med Fac Mannheim Comp Assisted Clin Med Heidelberg Germany Univ Magdeburg Fac Comp Sci Magdeburg Germany Univ Magdeburg Res Campus STIMULATE Magdeburg Germany

ISBN: (纸本)9781510625501

Multimodal registration improves surgical planning and the performance of interventional procedures such as transarterial chemoembolizations (FACE), since it allows to combine complementary information provided by pre- and intrainterventional data about tumor localization and access. However, no registration methods specifically developed for the multimodal registration of abdominal scans exist and as a result only general-purpose methods are available for this application. In this paper, we evaluate and optimize the performance or three standard registration methods which rely on different similarity metrics, namely Advanced Mattes Mutual Information (AMMI), Advanced Normalized Correlation (ANC) and Normalized Mutual Information (NMI), for the registration of preinterventional T1- and T2-weighted MRI to preinterventional CT as well as intrainterventional Cone Beam CT (CBCT) to preinterventional CT of the liver. Moreover, different variants of the registration algorithms, based on the introduction of masks and different resolution levels in multistage registrations, are investigated. To evaluate the performance of each registration method, the capture range was estimated based on the calculation of the mean target registration error.

关键词： image-guided interventions similarity metric multimodal registration TACE liver evaluation

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Tesseract-medical imaging: Open-Source Browser-based Platform for Artificial Intelligence Deployment in medical imaging

Tesseract-Medical Imaging: Open-Source Browser-based Platfor...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Sedghi, Alireza Hamidi, Soheil Mehrtash, Alireza Ziegler, Erik Tempany, Clare Pieper, Steve Kapur, Tina Mousavi, Parvin Queens Univ Med Informat Lab Kingston ON Canada Harvard Med Sch Radiol Dept Brigham & Womens Hosp Boston MA 02115 USA Univ British Columbia Dept Elect & Comp Engn Vancouver BC Canada Open Hlth Imaging Fdn Chicago IL USA

ISBN: (纸本)9781510625501

Artificial Intelligence (AI) is increasingly becoming a tool to enhance various medical image analysis tasks with accuracies comparable to expert clinicians. Computer assisted detection and diagnosis, and image segmentation and registration have significantly benefited from AI. However, integration of AI into the clinical workflow has been slow due to requirements for libraries that are specific to each model, and also environments that are specific to clinical centres. These challenges demonstrate the need for an AI-based solution that can be integrated into any environment with minimum hardware and software overhead. Tesseract-medicalimaging (Tesseract-MI) is an open-source, web-based platform which enables deployment of AI models while simultaneously providing standard image viewing and reporting schemes. The goal of Tesseract-MI is to augment 3D medical imaging and provide a 4th dimension (AI) when requested by a user. As a case study, we demonstrate the utility of our platform and present ProstateCancer..ai, a web application for identification of clinically significant prostate cancer in MRI.

关键词： Artificial intelligence medical imaging Magnetic resonance imaging Picture Archiving and Communication System Prostate Clinical research Integration Radiology

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Automated tumor assessment of squamous cell carcinoma on tongue cancer patients with hyperspectral imaging

Automated tumor assessment of squamous cell carcinoma on ton...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Manni, Francesca van der Sommen, Fons Zinger, Sveta Kho, Esther de Koning, Susan Brouwer Ruers, Theo Shan, Caifeng Schleipen, Jean de With, Peter H. N. Eindhoven Univ Technol POB 513 Eindhoven Netherlands Netherlands Canc Inst POB 90203 Amsterdam Netherlands Philips Res POB 80071 Eindhoven Netherlands

ISBN: (纸本)9781510625501

Head and neck cancer (HNC) includes cancers in the oral/nasal cavity, pharynx, larynx, etc., and it is the sixth most common cancer worldwide. The principal treatment is surgical removal where a complete tumor resection is crucial to reduce the recurrence and mortality rate. Intraoperative tumor imaging enables surgeons to objectively visualize the malignant lesion to maximize the tumor removal with healthy safe margins. Hyperspectral imaging (HSI) is an emerging imaging modality for cancer detection, which can augment surgical tumor inspection, currently limited to subjective visual inspection. In this paper, we aim to investigate HSI for automated cancer detection during image-guided surgery, because it can provide quantitative information about light interaction with biological tissues and exploit the potential for malignant tissue discrimination. The proposed solution forms a novel framework for automated tongue-cancer detection, explicitly exploiting HSI, which particularly uses the spectral variations in specific bands describing the cancerous tissue properties. The method follows a machine learning based classification, employing linear support vector machine (SVM), and offers a superior sensitivity and a significant decrease in computation time. The model evaluation is on 7 ex-vivo specimens of squamous cell carcinoma of the tongue, with known histology. The HSI combined with the proposed classification reaches a sensitivity of 94%, specificity of 68% and area under the curve (AUC) of 92%. This feasibility study paves the way for introducing HSI as a non-invasive imaging aid for cancer detection and increase of the effectiveness of surgical oncology.

关键词： hyperspectral imaging tongue cancer intraoperative tumor detection support vector machine image-guided surgery image classification cancer detection

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A dynamic mitral valve simulator for surgical training and patient specific preoperative planning

A dynamic mitral valve simulator for surgical training and p...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Boone, Nora Moore, John Ginty, Olivia Bainbridge, Daniel Eskandari, Mehdi Peters, Terry Western Univ Dept Med Sci London ON Canada Western Univ Robarts Res Inst London ON Canada Western Univ Dept Anesthesiol London ON Canada Western Univ Sch Biomed Engn London ON Canada Kings Coll Hosp London Denmark Hill London England

ISBN: (纸本)9781510625501

Mitral valve disease affects 2% of the Canadian population and 10% of those over the age of 75. Mitral valve regurgitation is a common valve disease often requiring surgical intervention for repair or replacement. Repair is often preferred over replacement, as it is associated with improved outcomes. Current mitral valve repair training is typically limited primarily to intraoperative experience. Additionally, the outcome of complex repair procedures is often unknown preoperatively, and is particularly true of new, off-pump repair techniques. Further challenges include identifying the most effective repair technique based on patient pathology, as multiple approaches exist. We present a hemodynamically accurate mitral valve phantom for testing previously validated patient specific pathological mitral valves. The device can be used for surgical resident training as well as complex procedure planning. The simulator is validated using pressure measurements across the mitral valve demonstrating realistic hemodynamics across a range of heart rates, and by evaluating valve function using 2D and 3D transesophageal echocardiography (TEE).

关键词： Heart 3D modeling Data modeling Silicon Surgery Pathology modeling 3D image processing Hemodynamics Cardiac imaging modeling and simulation

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Automatic applicator digitization for MRI-based cervical cancer brachytherapy planning using two surface models

Automatic applicator digitization for MRI-based cervical can...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Hrinivich, William T. Morcos, Marc Viswanathan, Akila McNutt, Todd Lee, Junghoon Johns Hopkins Univ Dept Radiat Oncol & Mol Radiat Sci Baltimore MD 21218 USA

ISBN: (纸本)9781510625501

Modern image-guided cervical cancer brachytherapy involves the insertion of hollow applicators in the uterus and surrounding the cervix to deliver a radioactive source. These applicators are imaged and manually digitized following insertion for treatment planning We present an algorithm to automatically digitize these applicators using MRI for cervical cancer brachytherapy planning. Applicators were digitized in vivo using T2-weighted MR images (1.5 T) from 21 brachytherapy fractions including 9 patients. The model-to-image registration algorithm was implemented in C++ involving a 2D matched filter to identify the applicator center, and a 3D surface model to identify local position by maximizing the intensity gradient normal to the surface. Surface models were produced using training MR images. Errors in the algorithm results were calculated as the 3D distances of the applicator tip and center from those identified manually A model based on manufacturer data was also used for applicator digitization to assess algorithm sensitivity to surface model variation. The algorithm correctly identified the applicator in 20 out of 21 images with mean execution time of 2.5 s. Mean +/- SD error following digitization using the MRI and manufacturer-based surface models was 1.2 +/- 0.6 mm and 1.3 +/- 0.7 mm for the tandem tip (p = 0.52), and 1.4 +/- 0.9 mm and 1.3 +/- 0.7 mm for the ring center (p = 0.61). The algorithm requires no manual initialization with consistent results across surface models, showing promise for clinical implementation.

关键词： brachytherapy MRI image-guided interventions radiotherapy

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StreoScenNet: Surgical Stereo robotic Scene segmentation

StreoScenNet: Surgical Stereo Robotic Scene segmentation

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Mohammed, Ahmed Yildirim, Sule Farup, Ivar Pedersen, Marius Hovde, Oistein Norwegian Univ Sci & Technol Norwegian Colour & Visual Comp Lab Trondheim Norway Norwegian Univ Sci & Technol Norwegian Informat Secur Lab Trondheim Norway Innlandet Hosp Trust Dept Gastroenterol Gjovik Norway Univ Oslo Inst Clin Med Oslo Norway

ISBN: (纸本)9781510625501

Surgical robot technology has revolutionized surgery toward a safer laparoscopic surgery and ideally been suited for surgeries requiring minimal invasiveness. Sematic segmentation from robot-assisted surgery videos is an essential task in many computer-assisted robotic surgical systems. Some of the applications include instrument detection, tracking and pose estimation. Usually, the left and right frames from the stereoscopic surgical instrument are used for semantic segmentation independently from each other. However, this approach is prone to poor segmentation since the stereo frames are not integrated for accurate estimation of the surgical scene. To cope with this problem, we proposed a multi encoder and single decoder convolutional neural network named StreoScenNet which exploits the left and right frames of the stereoscopic surgical system. The proposed architecture consists of multiple ResNet encoder blocks and a stacked convolutional decoder network connected with a novel sum-skip connection. The input to the network is a set of left and right frames and the output is a mask of the segmented regions for the left frame. It is trained end-to-end and the segmentation is achieved without the need of any pre-or post-processing. We compare the proposed architectures against state-of-the-art fully convolutional networks. We validate our methods using existing benchmark datasets that includes robotic instruments as well as anatomical objects and non -robotic surgical instruments. Compared with the previous instrument segmentation methods, our approach achieves a significant improved Dice similarity coefficient.

关键词： medical imaging da Vinci Surgical System Surgical instruments image segmentation Computer vision Deep learning

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Semi-Supervised image Registration using Deep Learning

Semi-Supervised Image Registration using Deep Learning

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Sedghi, Alireza Luo, Jie Mehrtash, Alireza Pieper, Steve Tempany, Clare M. Kapur, Tina Mousavi, Parvin Wells, William M., III Queens Univ Med Informat Lab Kingston ON Canada Harvard Med Sch Brigham & Womens Hosp Radiol Dept Boston MA 02115 USA Univ Tokyo Grad Sch Frontier Sci Tokyo Japan Univ British Columbia Dept Elect & Comp Engn Vancouver BC Canada

ISBN: (纸本)9781510625501

Deep metrics have been shown effective as similarity measures in multi-modal image registration;however, the metrics are currently constructed from aligned image pairs in the training data. In this paper, we propose a strategy for learning such metrics from roughly aligned training data. Symmetrizing the data corrects bias in the metric that results from misalignment in the data (at the expense of increased variance), while random perturbations to the data, i.e. dithering, ensures that the metric has a single mode, and is amenable to registration by optimization. Evaluation is performed on the task of registration on separate unseen test image pairs. The results demonstrate the feasibility of learning a useful deep metric from substantially misaligned training data, in some cases, the results are significantly better than from Mutual Information. Data augmentation via dithering is, therefore, an effective strategy for discharging the need for well-aligned training data;this brings deep learning based registration from the realm of supervised to semi-supervised machine learning.

关键词： image registration Magnetic resonance imaging Ultrasonography medical imaging Data processing Machine learning Rigid registration 3D image processing image fusion Network architectures

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The Effect of imaging and Tracking Parameters on Ultrasound Probe Calibration Robustness

The Effect of Imaging and Tracking Parameters on Ultrasound ...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Groves, Leah Rankin, Adam Peters, Terry Chen, Elvis C. S. Western Univ Sch Biomed Engn London ON Canada Western Univ Robarts Res Inst London ON Canada Western Univ Dept Med Biophys London ON Canada

ISBN: (纸本)9781510625501

Ultrasound-guided interventions are progressively incorporating additional augmented reality (AR) components to improve navigation.(1) A fundamental requirement to integrate ultrasound (US) images into AR environments is US probe calibration, which places images from a tracked US probe in the context of the tracker's coordinate system.(2) To improve the incompatibility of common US probe calibration methods with clinical environments, Chen et al. developed an US calibration method (GUScal) with a focus for intraoperative application.(3) To understand the effect of image quality and tracking accuracy on this calibration method, novice users were recruited to perform the calibration under three different conditions: (1) free-hand with one focal depth, (2) free-hand with three focal depths, and (3) using a mechanical arm to fix the needle with one focal depth. An expert user repeated this process 15 times per condition. The resultant transformation matrices and associated times were recorded for all calibrations. Numerical and visual analysis was conducted to compare the users calibrations results to each other and to the expert results. Based on our results we concluded including multiple focal depths produced the most precise calibrations for novice users. The expert user results showed that stabilizing the needle through a mechanical arm improved the calibration with practice. We recommend the inclusion of additional focal depths and a method to stabilize the needle to produce an accurate calibration in approximately 5 minutes.

关键词： Ultrasound calibration open-source robust image-guidance US-guidance augmented reality virtual reality

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Validation of two techniques for intraoperative hyperspectral human tissue determination

Validation of two techniques for intraoperative hyperspectra...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Wisotzky, Eric L. Kossack, Benjamin Uecker, Florian C. Arens, Philipp Dommerich, Steffen Hilsmann, Anna Eisert, Peter Fraunhofer Heinrich Hertz Inst Comp Vis & Graph Berlin Germany Humboldt Univ Visual Comp Berlin Germany Charite Univ Med Berlin Dept Otorhinolaryngol Berlin Germany

ISBN: (纸本)9781510625501

Hyperspectral imaging (HSI) is a non-contact optical imaging technique with the potential to serve as an intraoperative computer-aided diagnostic tool. This work analyzes the optical properties of visible structures in the surgical field for automatic tissue categorization. Building an HSI-based computer-aided tissue analysis system requires accurate ground truth and validation of optical soft tissue properties as these show large variability. In this paper, we introduce and validate two different hyperspectral intraoperative imaging setups and their use for the analysis of optical tissue properties. First, we present an improved multispectral filter-wheel setup integrated into a fully digital microscope. Second, we present a novel setup of two hyperspectral snapshot cameras for intraoperative usage. Both setups are operating in the spectral range of 400 nm up to 975 nm. They are calibrated and validated using the same database and calibration set. For validation, a color chart with 18 well-defined color spectra in the visual range is analyzed. Thus, the results acquired with both settings become transferable and comparable to each other as well as between different interventions. Clinical in-vivo data of two different oral and maxillofacial surgical procedures underline the potential of HSI as an intraoperative diagnostic tool and the clinical usability of both setups. Thereby, we demonstrate their feasibility for the in-vivo analysis and differentiation of different human soft tissues.

关键词： hyperspectral imaging multispectral imaging snapshot camera filter-wheel setup calibration human soft tissue tissue analysis

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