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

共 167 条记录，以下是131-140 订阅

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Surface-based prostate registration with biomechanical regularization

Surface-based prostate registration with biomechanical regul...

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

作者： van de Ven, Wendy J. M. Hu, Yipeng Barentsz, Jelle O. Karssemeijer, Nico Barratt, Dean Huisman, Henkjan J. Radboud Univ Nijmegen Med Ctr Dept Radiol NL-6525 ED Nijmegen Netherlands UCL Ctr Med Image Comp London England

ISBN: (纸本)9780819494450

Adding MR-derived information to standard transrectal ultrasound (TRUS) images for guiding prostate biopsy is of substantial clinical interest. A tumor visible on MR images can be projected on ultrasound by using MR-US registration. A common approach is to use surface-based registration. We hypothesize that biomechanical modeling will better control deformation inside the prostate than a regular surface-based registration method. We developed a novel method by extending a surface-based registration with finite element (FE) simulation to better predict internal deformation of the prostate. For each of six patients, a tetrahedral mesh was constructed from the manual prostate segmentation. Next, the internal prostate deformation was simulated using the derived radial surface displacement as boundary condition. The deformation field within the gland was calculated using the predicted FE node displacements and thin-plate spline interpolation. We tested our method on MR guided MR biopsy imaging data, as landmarks can easily be identified on MR images. For evaluation of the registration accuracy we used 45 anatomical landmarks located in all regions of the prostate. Our results show that the median target registration error of a surface-based registration with biomechanical regularization is 1.88 mm, which is significantly different from 2.61 mm without biomechanical regularization. We can conclude that biomechanical FE modeling has the potential to improve the accuracy of multimodal prostate registration when comparing it to regular surface-based registration.

关键词： Non-linear image registration Biomechanical modeling Finite element analysis Thin-plate splines Prostate cancer

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Patient-specific liver deformation modeling for tumor tracking

Patient-specific liver deformation modeling for tumor tracki...

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

作者： Oh, Young-Taek Hwang, Youngkyoo Kim, Jung-Bae Bang, Won-Chul Kim, James D. K. Kim, ChangYeong Samsung Adv Inst Technol Yongin 446712 Gyeonggi Do South Korea

ISBN: (纸本)9780819494450

We present a new method for patient-specific liver deformation modeling for tumor tracking. Our method focuses on deforming two main blood vessels of the liver - hepatic and portal vein - to utilize them as features. A novel centerline editing algorithm based on ellipse fitting is introduced for vessel deformation. Centerline-based blood vessel model and various interpolation methods are often used for generating a deformed model at the specific time t. However, it may introduce artifacts when models used in interpolation are not consistent. One of main reason of this inconsistency is the location of bifurcation points differs from each image. To solve this problem, our method generates a base model from one of patient's CT images. Next, we apply a rigid iterative closest point (ICP) method to the base model with centerlines of other images. Because the transformation is rigid, the length of each vessel's centerline is preserved while some part of the centerline is slightly deviated from centerlines of other images. We resolve this mismatch using our centerline editing algorithm. Finally, we interpolate three deformed models of liver, blood vessels, tumor using quadratic Bezier curves. We demonstrate the effectiveness of the proposed approach with the real patient data.

关键词： Tumor tracking Centerline editing Deformation Spline curve Interpolation

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Integration of Intraoperative and Model-Updated images into an Industry-Standard Neuronavigation System: Initial Results

Integration of Intraoperative and Model-Updated Images into ...

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

作者： Schaewe, Timothy J. Fan, Xiaoyao Ji, Songbai Hartov, Alex Holton, Leslie Hiemenz Roberts, David W. Paulsen, Keith D. Simon, David A. Medtronic Inc Surg Technol Louisville CO 80027 USA Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Dartmouth Coll Dartmouth Med Sch Hanover NH 03755 USA Dartmouth Coll Hitchcock Med Ctr Norris Cotton Canc Ctr Lebanon NH 03756 USA Dartmouth Coll Hitchcock Med Ctr Neurosurg Sect Lebanon NH 03756 USA

ISBN: (纸本)9780819494450

Dartmouth and Medtronic have established an academic-industrial partnership to develop, validate, and evaluate a multi-modality neurosurgical image-guidance platform for brain tumor resection surgery that is capable of updating the spatial relationships between preoperative images and the current surgical field. Previous studies have shown that brain shift compensation through a modeling framework using intraoperative ultrasound and/or visible light stereovision to update preoperative MRI appears to result in improved accuracy in navigation. However, image updates have thus far only been produced retrospective to surgery in large part because of gaps in the software integration and information flow between the co-registration and tracking, image acquisition and processing, and image warping tasks which are required during a case. This paper reports the first demonstration of integration of a deformation-based image updating process for brain shift modeling with an industry-standard image guided surgery platform. Specifically, we have completed the first and most critical data transfer operation to transmit volumetric image data generated by the Dartmouth brain shift modeling process to the Medtronic StealthStation (R) system. StealthStation (R) comparison views, which allow the surgeon to verify the correspondence of the received updated image volume relative to the preoperative MRI, are presented, along with other displays of image data such as the intraoperative 3D ultrasound used to update the model. These views and data represent the first time that externally acquired and manipulated image data has been imported into the StealthStation (R) system through the StealthLink (R) portal and visualized on the StealthStation (R) display.

关键词： image guided neurosurgery computational modeling intraoperative imaging brain shift estimation

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Retractor-Induced Brain Shift Compensation in image-guided Neurosurgery

Retractor-Induced Brain Shift Compensation in Image-guided N...

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

作者： Fan, Xiaoyao Ji, Songbai Hartov, Alex Roberts, David Paulsen, Keith Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Dartmouth Med Sch Hanover NH 03755 USA

ISBN: (纸本)9780819494450

In image-guided neurosurgery, intraoperative brain shift significantly degrades the accuracy of neuronavigation that is solely based on preoperative magnetic resonance images (pMR). To compensate for brain deformation and to maintain the accuracy in image guidance achieved at the start of surgery, biomechanical models have been developed to simulate brain deformation and to produce model-updated MR images (uMR) to compensate for brain shift. To-date, most studies have focused on shift compensation at early stages of surgery (i.e., updated images are only produced after craniotomy and durotomy). Simulating surgical events at later stages such as retraction and tissue resection are, perhaps, clinically more relevant because of the typically much larger magnitudes of brain deformation. However, these surgical events are substantially more complex in nature, thereby posing significant challenges in model-based brain shift compensation strategies. In this study, we present results from an initial investigation to simulate retractor-induced brain deformation through a biomechanical finite element (FE) model where whole-brain deformation assimilated from intraoperative data was used produce uMR for improved accuracy in image guidance. Specifically, intensity-encoded 3D surface profiles at the exposed cortical area were reconstructed from intraoperative stereovision (iSV) images before and after tissue retraction. Retractor-induced surface displacements were then derived by coregistering the surfaces and served as sparse displacement data to drive the FE model. With one patient case, we show that our technique is able to produce uMR that agrees well with the reconstructed iSV surface after retraction. The computational cost to simulate retractor-induced brain deformation was approximately 10 min. In addition, our approach introduces minimal interruption to the surgical workflow, suggesting the potential for its clinical application.

关键词： image-guided neurosurgery brain deformation computational modeling stereovision surface registration

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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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Fuzzy model-based body-wide anatomy recognition in medical images

Fuzzy model-based body-wide anatomy recognition in medical i...

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

作者： Udupa, Jayaram K. Odhner, Dewey Tong, Yubing Matsumoto, Monica M. S. Ciesielski, Krzysztof C. Vaideeswaran, Pavithra Ciesielski, Victoria Saboury, Babak Zhao, Liming Mohammadianrasanani, Syedmehrdad Torigian, Drew A. Univ Penn Med Image Proc Grp 423 Guardian DrBlockley Hall4th Floor Philadelphia PA 19104 USA Univ Penn Dept Radiol Philadelphia PA 19104 USA West Virginia Univ Dept Math Morgantown WV USA

ISBN: (纸本)9780819494450

To make Quantitative Radiology a reality in routine radiological practice, computerized automatic anatomy recognition (AAR) becomes essential. Previously, we presented a fuzzy object modeling strategy for AAR. This paper presents several advances in this project including streamlined definition of open-ended anatomic objects, extension to multiple imaging modalities, and demonstration of the same AAR approach on multiple body regions. The AAR approach consists of the following steps: (a) Collecting image data for each population group G and body region B. (b) Delineating in these images the objects in B to be modeled. (c) Building Fuzzy Object Models (FOMs) for B. (d) Recognizing individual objects in a given image of B by using the models. (e) Delineating the recognized objects. (f) Implementing the computationally intensive steps in a graphics processing unit (GPU). image data are collected for B and G from our existing patient image database. Fuzzy models for the individual objects are built and assembled into a model of B as per a chosen hierarchy of the objects in B. A global recognition strategy is used to determine the pose of the objects within a given image I following the hierarchy. The recognized pose is utilized to delineate the objects, also hierarchically. Based on three body regions tested utilizing both computed tomography (CT) and magnetic resonance (MR) imagery, recognition accuracy for non-sparse objects has been found to be generally sufficient (3 to 11 mm or 2-3 voxels) to yield delineation false positive (FP) and true positive (TP) values of < 5% and >= 90%, respectively. The sparse objects require further work to improve their recognition accuracy.

关键词： Shape modeling fuzzy models object recognition segmentation graph cut fuzzy connectedness

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Patient-specific port placement for laparoscopic surgery using atlas-based registration

Patient-specific port placement for laparoscopic surgery usi...

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

作者： Enquobahrie, Andinet Shivaprabhu, Vikas Aylward, Stephen Finet, Julien Cleary, Kevin Alterovitz, Ron Kitware Inc Clifton Pk NY 12065 USA Childrens Natl Med Ctr Washington DC 20010 USA Univ N Carolina Chapel Hill NC 27599 USA

ISBN: (纸本)9780819494450

Laparoscopic surgery is a minimally invasive surgical approach, in which abdominal surgical procedures are performed through trocars via small incisions. Patients benefit by reduced post-operative pain, shortened hospital stays, improved cosmetic results, and faster recovery times. Optimal port placement can improve surgeon dexterity and avoid the need to move the trocars, which would cause unnecessary trauma to the patient. We are building an intuitive open source visualization system to help surgeons identify ports. Our methodology is based on an intuitive port placement visualization module and atlas-based registration algorithm to transfer port locations to individual patients. The methodology follows three steps: 1) Use a port placement visualization module to manually place ports in an abdominal organ atlas. This step generates port-augmented abdominal atlas. This is done only once for a given patient population. 2) Register the atlas data with the patient CT data, to transfer the prescribed ports to the individual patient 3) Review and adjust the transferred port locations using the port placement visualization module. Tool maneuverability and target reachability can be tested using the visualization system. Our methodology would decrease the amount of physician input necessary to optimize port placement for each patient case. In a follow up work, we plan to use the transferred ports as starting point for further optimization of the port locations by formulating a cost function that will take into account factors such as tool dexterity and likelihood of collision between instruments.

关键词： Surgery Visualization Laparoscopy 3D modeling 3D acquisition Cameras Data modeling image registration Medical imaging Detection and tracking algorithms

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Medical Imaging 2013: image-guided procedures, robotic interventions, and modeling

Medical Imaging 2013: Image-Guided Procedures, Robotic Inter...

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Medical Imaging 2013: image-guided procedures, robotic interventions, and modeling

ISBN: (纸本)9780819494450

The proceedings contain 87 papers. The topics discussed include: technician-free system for image-guided bronchoscopy;robust feature tracking for endoscopic pose estimation and structure recovery;towards designing an optical-flow based colonoscopy tracking algorithm: a comparative study;image guidance system for flexible endoscopes considering tissue deformation;endoscopic laser range scanner for minimally invasive, mage guided kidney surgery;evaluation of non-rigid constrained CT/CBCT registration algorithms for delineation propagation in the context of prostate cancer radiotherapy;fast radioactive seed localization in intraoperative cone beam CT for low-dose-rate prostate brachytherapy;a dynamic dosimetry system for prostate brachytherapy;fully automated prostate magnetic resonance imaging and transrectal ultrasound fusion via a probabilistic registration metric;nonrigid liver registration for image-guided surgery using partial surface data: a novel iterative approach;cryo-balloon catheter localization in fluoroscopic images;and respiratory motion influence on catheter contact force during radio frequency ablation procedures.

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Progress in Biomedical Optics and Imaging - Proceedings of spie: Introduction

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of spie - The International Society for Optical Engineering 2013年 8671卷 xix-xx页

作者： Holmes III, David R. Yaniv, Ziv R.

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Medical robotics and Computer-Integrated Interventional Medicine

Medical Robotics and Computer-Integrated Interventional Medi...

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

作者： Taylor, Russell H. Johns Hopkins Univ 3400 N Charles St Baltimore MD 21218 USA

ISBN: (纸本)9780819489654

Computer-Integrated Interventional Medicine (CIIM) promises to have a profound impact on health care in the next 20 years, much as and for many of the same reasons that the marriage of computers and information processing methods with other technology have had on manufacturing, transportation, and other sectors of our society. Our basic premise is that the steps of creating patient-specific computational models, using these models for planning, registering the models and plans with the actual patient in the operating room, and using this information with appropriate technology to assist in carrying out and monitoring the intervention are best viewed as part of a complete patient-specific intervention process that occurs over many time scales. Further, the information generated in computer-integrated interventions can be captured and analyzed statistically to improve treatment processes. This paper will explore these themes briefly, using examples drawn from our work at the Engineering Research Center for Computer-Integrated Surgical Systems and Technology (CISST ERC).

关键词： Computer-Integrated Surgery Computer-Integrated interventions Medical robotics image-guided interventions Medical Imaging and modeling Experience Based Interventional Medicine

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