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

作者： Sun, Kaiqiong Udupa, Jayaram K. Odhner, Dewey Tong, Yubing Torigian, Drew A. Nanchang Hangkong Univ Comp Vis Lab Nanchang 330063 Peoples R China Univ Pennsylvania Med Image Proc Grp 423 Guardian DrBlockley Hall4th Floor Philadelphia PA 19104 USA Univ Pennsylvania Dept Radiol 423 Guardian DrBlockley Hall4th Floor Philadelphia PA 19104 USA

ISBN: (纸本)9780819498298

This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

关键词： Shape modeling fuzzy models object recognition fuzzy connectedness segmentation registration

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Dimensional accuracy of 3D printed vertebra

Dimensional accuracy of 3D printed vertebra

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

作者： Ogden, Kent Ordway, Nathaniel Diallo, Dalanda Tillapaugh-Fay, Gwen Aslan, Can SUNY Upstate Med Univ Dept Radiol 900 S Crouse Ave Syracuse NY 13210 USA SUNY Upstate Med Univ Dept Orthoped Surg Syracuse NY 13210 USA Syracuse Univ Dept Biomed & Chem Engn Syracuse NY 13210 USA

ISBN: (纸本)9780819498298

3D printer applications in the biomedical sciences and medical imaging are expanding and will have an increasing impact on the practice of medicine. Orthopedic and reconstructive surgery has been an obvious area for development of 3D printer applications as the segmentation of bony anatomy to generate printable models is relatively straightforward. There are important issues that should be addressed when using 3D printed models for applications that may affect patient care;in particular the dimensional accuracy of the printed parts needs to be high to avoid poor decisions being made prior to surgery or therapeutic procedures. In this work, the dimensional accuracy of 3D printed vertebral bodies derived from CT data for a cadaver spine is compared with direct measurements on the ex-vivo vertebra and with measurements made on the 3D rendered vertebra using commercial 3D image processing software. The vertebra was printed on a consumer grade 3D printer using an additive print process using PLA (polylactic acid) filament. Measurements were made for 15 different anatomic features of the vertebral body, including vertebral body height, endplate width and depth, pedicle height and width, and spinal canal width and depth, among others. It is shown that for the segmentation and printing process used, the results of measurements made on the 3D printed vertebral body are substantially the same as those produced by direct measurement on the vertebra and measurements made on the 3D rendered vertebra.

关键词： 3D printing orthopedic modeling dimensional accuracy vertebral modeling

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Target Registration Error for Rigid Shape-based Registration with Heteroscedastic Noise

Target Registration Error for Rigid Shape-based Registration...

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

作者： Ma, Burton Choi, Joy Huai, Hong Ming York Univ Dept Elect Engn & Comp Sci Toronto ON M3J 2R7 Canada

ISBN: (纸本)9780819498298

We propose an analytic equation for approximating expected root mean square (RMS) target registration error (TRE) for rigid shape-based registration where measured noisy data points are matched to a rigid shape. The noise distribution of the data points is assumed to be zero-mean, independent, and non-identical;i.e., the noise covariance may be different for each data point. The equation was derived by extending a previously published spatial stiffness model of registration. The equation was validated by performing registration experiments with both synthetic registration data and data collected using an optically tracked pointing stylus. The synthetic registration data were generated from the surface of an ellipsoid. The optically tracked data were collected from three plastic replicas of human radii and registered to isosurface models of the radii computed from CT scans. Noise covariances for the data points were computed by considering the pose of the tracked stylus, the positions of the individual fiducial markers on the stylus coordinate reference frame, and the calibrated position of the stylus tip;these quantities and an estimate of the fiducial localization covariance of the tracking system were used as inputs to a previously published algorithm for estimating the covariance of TRE for point-based (fiducial) registration. Registration simulations were performed using a modified version of the iterated closest point algorithm and the resulting RMS TREs were compared to the values predicted by our analytic equation.

关键词： image registration Mahalanobis distance Detection and tracking algorithms Error analysis Optical tracking Computed tomography Computer simulations Data modeling Calibration Computing systems

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Dynamic Tracking of a Deformable Tissue Based on 3D-2D MR-US image Registration

Dynamic Tracking of a Deformable Tissue Based on 3D-2D MR-US...

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

作者： Marami, Bahram Sirouspour, Shahin Fenster, Aaron Capson, David W. McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada Robert Res Inst Imaging Res Lab London ON N6A 5B7 Canada Univ Western Ontario Biomed Engn Grad Program London ON N6A 3K7 Canada Univ Victoria Dept Elect & Comp Engn Victoria BC V8W 2Y2 Canada

ISBN: (纸本)9780819498298

Real-time registration of pre-operative magnetic resonance (MR) or computed tomography (CT) images with intra-operative Ultrasound (US) images can be a valuable tool in image-guided therapies and interventions. This paper presents an automatic method for dynamically tracking the deformation of a soft tissue based on registering pre-operative three-dimensional (3D) MR images to intra-operative two-dimensional (2D) US images. The registration algorithm is based on concepts in state estimation where a dynamic finite element (FE)-based linear elastic deformation model correlates the imaging data in the spatial and temporal domains. A Kalman-like filtering process estimates the unknown deformation states of the soft tissue using the deformation model and a measure of error between the predicted and the observed intra-operative imaging data. The error is computed based on an intensity-based distance metric, namely, modality independent neighborhood descriptor (MIND), and no segmentation or feature extraction from images is required. The performance of the proposed method is evaluated by dynamically deforming 3D pre-operative MR images of a breast phantom tissue based on real-time 2D images obtained from an US probe. Experimental results on different registration scenarios showed that deformation tracking converges in a few iterations. The average target registration error on the plane of 2D US images for manually selected fiducial points was between 0.3 and 1.5 mm depending on the size of deformation.

关键词： Multimodal image registration 3D-2D MR-US registration image-guided intervention dynamic finite element modeling state estimation

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Marker-less Respiratory Motion modeling Using the Microsoft Kinect for Windows

Marker-less Respiratory Motion Modeling Using the Microsoft ...

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

作者： Tahavori, F. Alnowami, M. Wells, K. Univ Surrey Ctr Vis Speech & Signal Proc Guildford GU2 7XH Surrey England King Abdulaziz Univ Nucl Engn Dept Jeddah Saudi Arabia

ISBN: (纸本)9780819498298

Patient respiratory motion is a major problem during external beam radiotherapy of the thoracic and abdominal regions due to the associated organ and target motion. In addition, such motion introduces uncertainty in both radiotherapy planning and delivery and may potentially vary between the planning and delivery sessions. The aim of this work is to examine subject-specific external respiratory motion and its associated drift from an assumed average cycle which is the basis for many respiratory motion compensated applications including radiotherapy treatment planning and delivery. External respiratory motion data were acquired from a group of 20 volunteers using a marker-less 3D depth camera, Kinect for Windows. The anterior surface encompassing thoracic and abdominal regions were subject to principal component analysis (PCA) to investigate dominant variations. The first principal component typically describes more than 70% of the motion data variance in the thoracic and abdominal surfaces. Across all of the subjects used in this study, 58% of subjects demonstrate largely abdominal breathing and 33% exhibited largely thoracic dominated breathing. In most cases there is observable drift in respiratory motion during the 300s capture period, which is visually demonstrated using Kernel Density Estimation. This study demonstrates that for this cohort of apparently healthy volunteers, there is significant respiratory motion drift in most cases, in terms of amplitude and relative displacement between the thoracic and abdominal respiratory components. This has implications for the development of effective motion compensation methodology.

关键词： Principal component analysis Radiotherapy Cameras Motion models Motion analysis Motion estimation Stereoscopic cameras Chest Visualization Visual process modeling

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Intraoperative imaging of cortical perfusion by time-resolved thermography using cold bolus approach

Intraoperative imaging of cortical perfusion by time-resolve...

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

作者： Hollmach, Julia Schnabel, Christian Hoffmann, Nico Radev, Yordan Sobottka, Stephan Kirsch, Matthias Schackert, Gabriele Koch, Edmund Steiner, Gerald Tech Univ Dresden Klin Sensoring & Monitoring D-01307 Dresden Germany Techn Univ Dresden Klin & Poliklinik Neurochirurgie D-01307 Dresden Germany

ISBN: (纸本)9780819498298

During the past decade, thermographic cameras with high thermal and temporal resolution of up to 30 mK and 50 Hz, respectively, have been developed. These camera systems can be used to reveal thermal variations and heterogeneities of tissue and blood. Thus, they provide a fast, sensitive, noninvasive, and label-free application to investigate blood perfusion and to detect perfusion disorders. Therefore, time-resolved thermography is evaluated and tested for intraoperative imaging of the cerebral cortex during neurosurgeries. The motivation of this study is the intraoperative evaluation of the cortical perfusion by observing the temporal temperature curve of the cortex during and after the intravenous application of a cold bolus. The temperature curve caused by a cold bolus is influenced by thermodilution, depending on the temperature difference to the patient's circulation, and the pattern of mixing with the patient's blood. In this initial study, a flow phantom was used in order to determine the temperature variations of cold boli under stable conditions in a vascular system. The typical temperature profile of cold water passing by can be approximated by a biGaussian function involving a set of four parameters. These parameters can be used to assess the cold bolus, since they provide information about its intensity, duration and arrival time. The findings of the flow phantom can be applied to thermographic measurements of the human cortex. The results demonstrate that time-resolved thermographic imaging is a suitable method to detect cold boli not only at a flow phantom but also at the human cortex.

关键词： Thermography Blood Thermal modeling Cameras Imaging systems Temperature metrology Tissues Epilepsy Heat treatments In vivo imaging

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Medical Imaging 2014: image-guided procedures, robotic interventions, and modeling

Medical Imaging 2014: Image-Guided Procedures, Robotic Inter...

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Medical Imaging 2014: image-guided procedures, robotic interventions, and modeling

ISBN: (纸本)9780819498298

The proceedings contain 98 papers. The topics discussed include: adaptive fiducial-free registration using multiple point selection for real-time electromagnetically navigated endoscopy;geometric estimation of intestinal contraction for motion tracking of video capsule endoscope;motion magnification for endoscopic surgery;reconstruction and feature selection for desorption electrospray ionization mass spectroscopy imagery;automatic standard plane adjustment on mobile C-Arm CT images of the calcaneus using atlas-based feature registration;mechanically assisted 3D ultrasound for pre-operative assessment and guiding percutaneous treatment of focal liver tumors;optoacoustic sensing for target detection inside cylindrical catheters;and polarization-sensitive multispectral tissue characterization for optimizing intestinal anastomosis.

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Exciting Progress in the Growth of JMI

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JOURNAL OF MEDICAL IMAGING 2014年第2期1卷 020101页

作者： Giger, Maryellen L. The Univ. of Chicago (United States)

Welcome to the second issue of the spie Journal of Medical Imaging (JMI). As of this writing, we have received 146 submissions from 28 countries—from major institutions worldwide. I believe we are on track in accomplishing our goals for the journal as the manuscripts submitted thus far span the various fields of medical imaging. For example, this second issue includes excellent papers on image processing; computer-aided diagnosis; image-guided procedures, robotic interventions and modeling; image perception, observer performance, and technology; ultrasonic imaging and tomography; digital pathology; and biomedical applications in molecular, structural, and functional imaging. We also publish our first book review.

关键词： Medical imaging Biomedical optics Digital image processing Functional imaging image processing Pathology Performance modeling robotics Tomography Ultrasonography

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A patient specific 4D MRI liver motion model based on sparse imaging and registration

A patient specific 4D MRI liver motion model based on sparse...

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

作者： Noorda, Yolanda H. Bartels, Lambertus W. van Stralen, Marijn Pluim, Josien P. W. Univ Med Ctr Utrecht Image Sci Inst Utrecht Netherlands

ISBN: (纸本)9780819494450

Introduction image-guided minimally invasive procedures are becoming increasingly popular. Currently, High-Intensity Focused Ultrasound (HIFU) treatment of lesions in mobile organs, such as the liver, is in development. A requirement for such treatment is automatic motion tracking, such that the position of the lesion can be followed in real time. We propose a 4D liver motion model, which can be used during planning of this procedure. During treatment, the model can serve as a motion predictor. In a similar fashion, this model could be used for radiotherapy treatment of the liver. Method The model is built by acquiring 2D dynamic sagittal MRI data at six locations in the liver. By registering these dynamics to a 3D MRI liver image, 2D deformation fields are obtained at every location. The 2D fields are ordered according to the position of the liver at that specific time point, such that liver motion during an average breathing period can be simulated. This way, a sparse deformation field is created over time. This deformation field is finally interpolated over the entire volume, yielding a 4D motion model. Results The accuracy of the model is evaluated by comparing unseen slices to the slice predicted by the model at that specific location and phase in the breathing cycle. The mean Dice coefficient of the liver regions was 0.90. The mean misalignment of the vessels was 1.9 mm. Conclusion The model is able to predict patient specific deformations of the liver and can predict regular motion accurately.

关键词： motion modeling registration MRI

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image-based modeling and Characterization of RF Ablation Lesions in Cardiac Arrhythmia Therapy

Image-based Modeling and Characterization of RF Ablation Les...

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

作者： Linte, Cristian A. Camp, Jon J. Rettmann, Maryam E. Holmes, David R., III Robb, Richard A. Mayo Clin Dep Physiol & Biomed Engn 200 1st St SW Rochester MN 55902 USA Mayo Clin Dep Physiol & Biomed Engn Rochester MN 55901 USA

ISBN: (纸本)9780819494450

In spite of significant efforts to enhance guidance for catheter navigation, limited research has been conducted to consider the changes that occur in the tissue during ablation as means to provide useful feedback on the progression of therapy delivery. We propose a technique to visualize lesion progression and monitor the effects of the RF energy delivery using a surrogate thermal ablation model. The model incorporates both physical and physiological tissue parameters, and uses heat transfer principles to estimate temperature distribution in the tissue and geometry of the generated lesion in near real time. The ablation model has been calibrated and evaluated using ex vivo beef muscle tissue in a clinically relevant ablation protocol. To validate the model, the predicted temperature distribution was assessed against that measured directly using fiberoptic temperature probes inserted in the tissue. Moreover, the model-predicted lesions were compared to the lesions observed in the post-ablation digital images. Results showed an agreement within 5 C between the model-predicted and experimentally measured tissue temperatures, as well as comparable predicted and observed lesion characteristics and geometry. These results suggest that the proposed technique is capable of providing reasonably accurate and sufficiently fast representations of the created RF ablation lesions, to generate lesion maps in near real time. These maps can be used to guide the placement of successive lesions to ensure continuous and enduring suppression of the arrhythmic pathway.

关键词： image-guided Cardiac procedures Data Integration for the Clinic/OR image-guided Cardiac Ablation Intra-operative modeling and Monitoring Evaluation and Validation Intra-procedure Visualization

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