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

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Data Fusion for Planning Target Volume and Isodose Prediction in Prostate Brachytherapy

Data Fusion for Planning Target Volume and Isodose Predictio...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Nouranian, Saman Ramezani, Mahdi Mahdavi, S. Sara Spadinger, Ingrid Morris, William J. Salcudean, Septimiu E. Abolmaesumi, Purang Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada British Columbia Canc Agcy Vancouver Canc Ctr Vancouver BC V5Z 4E6 Canada

ISBN: (纸本)9781628415056

In low-dose prostate brachytherapy treatment, a large number of radioactive seeds is implanted in and adjacent to the prostate gland. Planning of this treatment involves the determination of a Planning Target Volume (PTV), followed by defining the optimal number of seeds, needles and their coordinates for implantation. The two major planning tasks, i.e. PTV determination and seed definition, are associated with inter- and intra-expert variability. Moreover, since these two steps are performed in sequence, the variability is accumulated in the overall treatment plan. In this paper, we introduce a model based on a data fusion technique that enables joint determination of PTV and the minimum Prescribed Isodose (mPD) map. The model captures the correlation between different information modalities consisting of transrectal ultrasound (TRUS) volumes, PTV and isodose contours. We take advantage of joint Independent Component Analysis (jICA) as a linear decomposition technique to obtain a set of joint components that optimally describe such correlation. We perform a component stability analysis to generate a model with stable parameters that predicts the PTV and isodose contours solely based on a new patient TRUS volume. We propose a framework for both modeling and prediction processes and evaluate it on a dataset of 60 brachytherapy treatment records. We show PTV prediction error of 10.02 +/- 4.5% and the V100 isodose overlap of 97 +/- 3.55% with respect to the clinical gold standard.

关键词： Prostate Data modeling Independent component analysis Process modeling Binary data Error analysis Data fusion Gold Cancer Reconstruction algorithms

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Computational modeling of Radiofrequency Ablation: Evaluation on Ex Vivo Data Using Ultrasound Monitoring

Computational Modeling of Radiofrequency Ablation: Evaluatio...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Audigier, Chloe Kim, Younsu Dillow, Austin Boctor, Emad M. Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA Johns Hopkins Univ Dept Radiol Baltimore MD 21218 USA Johns Hopkins Univ Dept Mech Engn Baltimore MD 21218 USA

ISBN: (数字)9781510607163

ISBN: (纸本)9781510607156;9781510607163

Radiofrequency ablation (RFA) is the most widely used minimally invasive ablative therapy for liver cancer, but it is challenged by a lack of patient-specific monitoring. Inter-patient tissue variability and the presence of blood vessels make the prediction of the RFA difficult. A monitoring tool which can be personalized for a given patient during the intervention would be helpful to achieve a complete tumor ablation. However, the clinicians do not have access to such a tool, which results in incomplete treatment and a large number of recurrences. Computational models can simulate the phenomena and mechanisms governing this therapy. The temperature evolution as well as the resulted ablation can be modeled. When combined together with intra-operative measurements, computational modeling becomes an accurate and powerful tool to gain quantitative understanding and to enable improvements in the ongoing clinical settings. This paper shows how computational models of RFA can be evaluated using intra-operative measurements. First, simulations are used to demonstrate the feasibility of the method, which is then evaluated on two ex vivo datasets. RFA is simulated on a simplified geometry to generate realistic longitudinal temperature maps and the resulted necrosis. Computed temperatures are compared with the temperature evolution recorded using thermometers, and with temperatures monitored by ultrasound (US) in a 2D plane containing the ablation tip. Two ablations are performed on two cadaveric bovine livers, and we achieve error of 2.2 degrees C on average between the computed and the thermistors temperature and 1.4 degrees C and 2.7 degrees C on average between the temperature computed and monitored by US during the ablation at two different time points (t = 240 s and t = 900 s).

关键词： Radiofrequency ablation Computational modeling Ultrasound thermal monitoring Ex vivo Validation

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Neurosurgery Simulation Using Non-linear Finite Element modeling and Haptic Interaction

Neurosurgery Simulation Using Non-linear Finite Element Mode...

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Lee, Huai-Ping Audette, Michel Joldes, Grand Roman Enquobahrie, Andinet Kitware Inc Clifton Pk NY 12065 USA Univ N Carolina Dept Comp Sci Chapel Hill NC 27599 USA Old Dominion Univ Dept MSVE Norfolk VA 23529 USA Univ Western Australia Sch Mech Engn Perth WA Australia

ISBN: (纸本)9780819489654

Real-time surgical simulation is becoming an important component of surgical training. To meet the real-time requirement, however, the accuracy of the biomechancial modeling of soft tissue is often compromised due to computing resource constraints. Furthermore, haptic integration presents an additional challenge with its requirement for a high update rate. As a result, most real-time surgical simulation systems employ a linear elasticity model, simplified numerical methods such as the boundary element method or spring-particle systems, and coarse volumetric meshes. However, these systems are not clinically realistic. We present here an on-going work aimed at developing an efficient and physically realistic neurosurgery simulator using a non-linear finite element method (FEM) with haptic interaction. Real-time finite element analysis is achieved by utilizing the total Lagrangian explicit dynamic (TLED) formulation and GPU acceleration of per-node and per-element operations. We employ a virtual coupling method for separating deformable body simulation and collision detection from haptic rendering, which needs to be updated at a much higher rate than the visual simulation. The system provides accurate biomechancial modeling of soft tissue while retaining a real-time performance with haptic interaction. However, our experiments showed that the stability of the simulator depends heavily on the material property of the tissue and the speed of colliding objects. Hence, additional efforts including dynamic relaxation are required to improve the stability of the system.

关键词： surgical simulation non-linear biomechanics finite element method haptic rendering

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Electromagnetically tracked partial nephrectomy navigation: demonstration of concept

Electromagnetically tracked partial nephrectomy navigation: ...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Lia, Hillary Baum, Zachary Vaughan, Thomas Ungi, Tamas McGregor, Thomas Fichtinger, Gabor Queens Univ Lab Percutaneous Surg Sch Comp Kingston ON Canada Queens Univ Dept Urol Kingston ON Canada

ISBN: (纸本)9781510625501

PURPOSE: Partial nephrectomy is the preferred method for managing small renal masses. This procedure has significant advantages over radical nephrectomy. However, partial nephrectomy is under-used due to its difficulty. We propose a navigation system for laparoscopic partial nephrectomy. In this study, we evaluate the usability and accuracy of the navigation system. METHODS: An electromagnetically tracked navigation system for partial nephrectomy was developed. This system tracks the positions of the laparoscopic scissors, ultrasound probe, tumor, and calyces and vasculature. Phantom kidneys were created using mixtures of plastisol and cellulose. To test the system, the navigation display quality was measured through measurement of lag and frames per second displayed. The accuracy of the system was determined through fiducial registration. Finally, a study consisting of ten participants was conducted to assess the usability of the navigation system using the System Usability Survey. RESULTS: The mean System Usability Score of the navigation system was 82.5. The navigation display had an average lag of 243 milliseconds and showed 5 frames per second. The accuracy was measured with fiducial registration and found to have an RMS error of 2.84 mm. CONCLUSION: The results of this study suggest that the partial nephrectomy navigation system developed is both usable and accurate. Future work will include the conversion of the laparoscopic scissor tool tracking to optical. Further studies will be conducted to determine the effectiveness of this technology in tumor resection and avoidance of calyx and vasculature damage. We will additionally explore this system as a training tool.

关键词： Laparoscopy Kidney Navigation systems Ultrasonography Tumors image segmentation 3D modeling Surgery Optical tracking Electromagnetism

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A personalized approach for microwave ablation treatment planning fusing radiomics and bioheat transfer modeling

A personalized approach for microwave ablation treatment pla...

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Medical Imaging conference - image-guided procedures, robotic interventions, and modeling

作者： Taeprasartsit, Pinyo Pathompatai, Chanok Jusomjai, Kasidit Wibowo, Henky Sebek, Jan Prakash, Punit Silpakorn Univ Fac Sci Dept Comp Bangkok 73000 Thailand Kansas State Univ Dept Elect & Comp Engn Manhattan KS 66506 USA PhenoMapper LLC San Jose CA 95120 USA Czech Tech Univ Dept Circuit Theory Prague Czech Republic

ISBN: (纸本)9781510633988

The use of percutaneous and bronchoscopic microwave ablation to treat both primary and secondary lung tumors has been growing recently. These ablation systems are typically accompanied by an ablation planning system to optimize the treatment outcome by ensuring adequate margin in the expected ablation zone during the planning phase. The planning system utilizes pre-operative CT scan to identify the tumor and recommend microwave probe position. Radiomics is a process of converting medical images into higher-dimensional data and subsequent mining of data to reveal underlying pathophysiology for enhancing clinical decision support making Radiomics analysis have shown promises in capturing distinct tumor characteristics and predicting prognosis of the tumor. Here, we present a new method to predict microwave ablation zones by supplementing a bioheat transfer model of microwave tissue ablation with microwave sensitive radiomics features. We hypothesize that supplementing traditional bioheat transfer modeling with microwave sensitive radiomics features will generate a more accurate and personalized ablation prediction that will lead to better treatment outcome. Inputs to the bioheat transfer modeling approach include the geometry of the target tumor, physical characteristics of the tissue, and dimensions of the microwave ablation applicator. The radiomics algorithm extracts characteristics of the targeted tumor's size and shape, as well as texture characteristics, from pre-operative CT images. We employed cascaded segmentation based on RetinaNet and U-Net to obtain a tumor's size and shape. Then, a segmented tumor is employed for texture analysis through a set of regression convolutional neural networks. These tumor characteristics are employed as radiomics features for more accurate dose prediction and margin for microwave ablation treatment. We present the preliminary results of a study using images from clinical lung tumor cases to predict ablation treatment outcome, w

关键词： radiomics microwave ablation dose prediction

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Spherical Harmonics for modeling Shape Transformations of Breasts following Breast Surgery

Spherical Harmonics for Modeling Shape Transformations of Br...

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Medical Imaging conference - image-guided procedures, robotic interventions, and modeling

作者： Sampathkumar, U. Nowroozilarki, Z. Reece, G. P. Hanson, S. E. Merchant, F. A. Univ Houston Dept Comp Sci Houston TX 77204 USA Univ Houston Dept Engn Technol Houston TX USA MD Anderson Canc Ctr Dept Plast Surg Houston TX USA

ISBN: (纸本)9781510633988

Breast shape aesthetic is most desired outcome of cosmetic and reconstructive breast surgery. Post-operative (post-op) patient satisfaction largely depends on patient expectations, hence appropriately communicating information about surgical options to patients and moderating patient expectations is critical in surgical planning. Breast modeling and computational simulation can help mitigate this challenge and provide an effective tool for presenting potential surgical outcomes and eliciting patient preferences. Most available computational models lack the ability to provide realistic estimation of breast shape changes. We have previously developed a Fourier spherical harmonics (SPHARM) based computational approach to model breast shape'. SPHARM modeling results in 1320 coefficients that are effective descriptors of the 3D breast shape. In this study, we develop a framework to transform the SPHARM coefficients of the pre-operative (pre-op) breast to generate an estimation of the post-op breast shape for cosmetic (e.g. implant-based augmentation) and reconstructive (e.g. implant, autologous tissue, etc.) surgery procedures. Least squares optimization was used to realize the transformation between the pre- and post-op SPHARM coefficients. We demonstrate the feasibility of our approach using data from patients who have undergone bilateral implant-based breast reconstruction as part of cancer treatment. We trained a random forest regression function using SPHARM coefficients and their corresponding shape transformation vectors for 21 pre op breasts and validated the regressor using a test dataset of 41 breasts. Our preliminary results demonstrate feasibility of the proposed data-driven approach to model transformation of the pre-op breast to its post-op form for a given surgical procedure.

关键词： Breast shape transformation modeling SPHARM Spherical harmonics Random forest regression

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Evaluation of three 3D US calibration methods

Evaluation of three 3D US calibration methods

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Hummel, Johann Kaar, Marcus Hoffmann, Rainer Bhatia, Amon Birkfellner, Wolfgang Figl, Michael Med Univ Vienna Ctr Med Phys & Biomed Engn Vienna Austria

ISBN: (纸本)9780819494450

With the introduction of 3D US image devices the demand for accurate and fast 3D calibration methods arose. We implemented three different calibration methods and compared the calibration results in terms of fiducial registration error (FRE) and target registration error (TRE). The three calibration methods included a multi-points phantom (MP), a feature based model (FM) and a membrane model (MM). With respect to the sphere method a simple point-to-point registration was applied. For the feature based model we employed a phantom consisting of spheres, pyramids and cones. These objects were imaged from different angles and a 3D3D registration was applied for all possible image combinations. The last method was accomplished by imaging a simple membrane which allows for calculation of the calibration matrix. For a first evaluation we computed the FRE for each method. To assess the calibration success on real patient data we used ten 3D3D registrations between images from the prostate. The FRE for the sphere method amounted to 1.40 mm, for the figure method to 1.05 mm and with respect to the membrane method to 1.12 mm. The deviation arising from ten 3D3D patient registration were 3.44 mm (MP), 2.93 mm (FM)and 2.84 mm (MM). The MM revealed to be the most accurate of the evaluated procedure while the MP has shown significant higher errors. The results from FM were close to the one from MM and also significant better than the one with the SM. Between FM and MM no significant difference was to detect.

关键词： Calibration image registration Optical spheres Ultrasonography Fermium Frequency modulation 3D image processing 3D acquisition 3D modeling Optical tracking

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Model-based correction for brain shift in deep brain stimulation burr hole procedures: a comparison using interventional magnetic resonance imaging

Model-based correction for brain shift in deep brain stimula...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Luo, Ma Narasimhan, Saramati Martin, Alastair J. Larson, Paul S. Miga, Michael I. Vanderbilt Univ Dept Biomed Engn Nashville TN 37235 USA Univ Calif San Francisco Dept Radiol & Biomed Imaging San Francisco CA 94143 USA Univ Calif San Francisco Dept Neurol San Francisco CA USA Vanderbilt Univ Med Ctr Dept Neurol Surg Nashville TN USA Vanderbilt Univ Med Ctr Dept Radiol Nashville TN 37232 USA Vanderbilt Univ Vanderbilt Inst Surg & Engn 221 Kirkland Hall Nashville TN 37235 USA

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

Deep brain stimulation (DBS) is an effective treatment for movement disorders, e.g. Parkinson's disease. The quality of DBS treatment is dependent on the implantation accuracy of DBS electrode leads into target structures. However, brain shift during burr hole procedures has been documented and hypothesized to negatively impact treatment quality. Several approaches have been proposed to compensate for brain shift in DBS, namely microelectrode recording (MER) and interventional magnetic resonance (iMR) imaging. Though both demonstrate benefits in guiding accurate electrode placement, they suffer drawbacks such as prolonged procedures and in the latter, cost considerations. Hence, we are exploring a model-based brain shift compensation strategy in DBS to improve targeting accuracy for surgical navigation. Our method is a deformation-atlas-based approach, i.e. potential intraoperative deformations are pre-computed via biomechanical model under varying conditions, combined with an inverse problem driven by sparse intraoperative data for estimating volumetric brain deformations. In this preliminary feasibility study, we examine our model's ability to predict brain shift in DBS by comparing with iMR in one patient. The evaluation includes: (1) a subsurface deformation comparison where subsurface shifts measured by iMR are compared to model-predicted counterparts;(2) a second comparison at surgical targets where the atlas-method is compared to deformations measured by non-rigid image-to-image registration using preoperative image and iMR. For the former, the model reduces alignment error from 8.6 +/- 1.4 to 3.6 +/- 0.8 mm, representing similar to 58.6% correction. For the latter, model estimated brain shifts at surgical targets are 2.4 and 0.6 mm, consistent with clinical observations.

关键词： Brain shift deep brain stimulation neurosurgery finite element computational modeling

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Medical Imaging 2012: image-guided procedures, robotic interventions, and modeling

Medical Imaging 2012: Image-Guided Procedures, Robotic Inter...

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Medical Imaging 2012: image-guided procedures, robotic interventions, and modeling

ISBN: (纸本)9780819489654

The proceedings contain 120 papers. The topics discussed include: deformable registration of the inflated and deflated lung for cone-beam CT-guided thoracic surgery;incorporation of prior knowledge for region of change imaging from sparse scan data in image-guided surgery;GPU-based iterative relative fuzzy connectedness image segmentation;automated volume of interest delineation and rendering of cone beam CT images in interventional cardiology;tracker-on-C for cone-beam CT-guided surgery: evaluation of geometric accuracy and clinical applications;medical robotics and computer-integrated interventional medicine;the role of three-dimensional visualization in robotics-assisted cardiac surgery;evaluation of deformation accuracy of a virtual pneumoperitoneum method based on clinical trials for patient-specific laparoscopic surgery simulator;and a method for constructing real-time FEM-based simulator of stomach behavior with large-scale deformation by neural networks.

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Medical Imaging 2022: image-guided procedures, robotic interventions, and modeling

Medical Imaging 2022: Image-Guided Procedures, Robotic Inter...

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Medical Imaging 2022: image-guided procedures, robotic interventions, and modeling

ISBN: (纸本)9781510649439

The proceedings contain 96 papers. The topics discussed include: from tool to assistant: towards developing adaptive surgical robots for the operating room;errors of type or errors of degree? cortical point targeting in transcranial magnetic stimulation;a new deep neural segmentation network for cerebral aneurysms in 2D digital subtraction angiography;patient registration using intraoperative stereovision for open cranial surgery;deformable registration of mri to intraoperative cone-beam CT of the brain using a joint synthesis and registration network;design of a modular, multi-arm concentric tube robot featuring roller gears;surgical navigation system for image-guided transoral robotic surgery: a proof of concept;image-guided system for radial-probe endobronchial ultrasound bronchoscopy;and real-time flexible endoscope navigation within bladder phantom having sparse non-distinct features is enhanced with robotic control.

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