@article {Ungi2020, title = {Automatic spine ultrasound segmentation for scoliosis visualization and measurement}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {67}, number = {11}, year = {2020}, month = {03/2020}, pages = {3234 - 3241}, abstract = {

Objective: Integrate tracked ultrasound and AI methods to provide a safer and more accessible alternative to X-ray for scoliosis measurement. We propose automatic ultrasound segmentation for 3-dimensional spine visualization and scoliosis measurement to address difficulties in using ultrasound for spine imaging. Methods: We trained a convolutional neural network for spine segmentation on ultrasound scans using data from eight healthy adult volunteers. We tested the trained network on eight pediatric patients. We evaluated image segmentation and 3-dimensional volume reconstruction for scoliosis measurement. Results: As expected, fuzzy segmentation metrics reduced when trained networks were translated from healthy volunteers to patients. Recall decreased from 0.72 to 0.64 (8.2\% decrease), and precision from 0.31 to 0.27 (3.7\% decrease). However, after finding optimal thresholds for prediction maps, binary segmentation metrics performed better on patient data. Recall decreased from 0.98 to 0.97 (1.6\% decrease), and precision from 0.10 to 0.06 (4.5\% decrease). Segmentation prediction maps were reconstructed to 3-dimensional volumes and scoliosis was measured in all patients. Measurement in these reconstructions took less than 1 minute and had a maximum error of 2.2{\textdegree} compared to X-ray. Conclusion: automatic spine segmentation makes scoliosis measurement both efficient and accurate in tracked ultrasound scans. Significance: Automatic segmentation may overcome the limitations of tracked ultrasound that so far prevented its use as an alternative of X-ray in scoliosis measurement.

}, doi = {10.1109/TBME.2020.2980540}, url = {https://ieeexplore.ieee.org/document/9034149}, author = {Tamas Ungi and Hastings Greer and Kyle R. Sunderland and Victoria Wu and Zachary M C Baum and Christopher Schlenger and Matthew Oetgen and Kevin Cleary and Stephen Aylward and Gabor Fichtinger} } @conference {Foroughi2008b, title = {Automatic initialization for 3D bone registration}, booktitle = {Medical Imaging 2008: Visualization, Image-guided Procedures, and Modeling}, volume = {6918}, number = {1}, year = {2008}, pages = {69182P}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 772632}, url = {http://link aip org/link/?PSI/6918/69182P/1}, author = {Pezhman Foroughi and Russell H. Taylor and Gabor Fichtinger}, editor = {Michael I. Miga and Kevin Cleary} } @article {Kettenbach2008, title = {Ultrasound-, CT-, MR-Guided Robot-Assisted Interventions}, journal = {Image Processing in Radiology}, volume = {3}, year = {2008}, pages = {393-409}, author = {Joachim Kettenbach and Gernot Kronreif and Andreas Melzer and Gabor Fichtinger and Dan Stoianovici and Kevin Cleary} } @article {DiMaio2007b, title = {Challenges in image-guided therapy system design}, journal = {Neuroimage}, volume = {37 Suppl 1}, year = {2007}, pages = {S144{\textendash}S151}, publisher = {Brigham, Women{\textquoteright}s Hospital, 75 Francis St , Boston, MA 02115, USA simond@bwh harvard edu}, abstract = {

System development for image-guided therapy (IGT), or image-guided interventions (IGI), continues to be an area of active interest across academic, industry groups This is an emerging field that is growing rapidly: major academic institutions, medical device manufacturers have produced IGT technologies that are in routine clinical use, dozens of high-impact publications are published in well regarded journals each year, and several small companies have successfully commercialized sophisticated IGT systems In meetings between IGT investigators over the last two years, a consensus has emerged that several key areas must be addressed collaboratively by the community to reach the next level of impact, efficiency in IGT research, development to improve patient care These meetings culminated in a two-day workshop that brought together several academic, industrial leaders in the field today The goals of the workshop were to identify gaps in the engineering infrastructure available to IGT researchers, develop the role of research funding agencies, the recently established US-based National Center for Image Guided Therapy (NCIGT), and ultimately to facilitate the transfer of technology among research centers that are sponsored by the National Institutes of Health (NIH) Workshop discussions spanned many of the current challenges in the development, deployment of new IGT systems Key challenges were identified in a number of areas, including: validation standards; workflows, use-cases, and application requirements; component reusability;, device interface standards This report elaborates on these key points, proposes research challenges that are to be addressed by a joint effort between academic, industry, and NIH participants

}, keywords = {adverse effects/instrumentation/trends, Algorithms, Computational Biology, Computer Systems, Computer-Assisted, Humans, instrumentation/trends, Knowledge Bases, Models, National Institutes of Health (U S ), Neurosurgical Procedures, Organizational, Outcome Assessment (Health Care), Reproducibility of Results, Robotics, Software, Surgery, Treatment Outcome, United States}, doi = {10 1016/j neuroimage 2007 04 026}, url = {http://dx doi org/10 1016/j neuroimage 2007 04 026}, author = {Simon DiMaio and Tina Kapur and Kevin Cleary and Stephen Aylward and Peter Kazanzides and Kirby Vosburgh and Randy Ellis and James Duncan and Keyvan Farahani and Heinz Lemke and T. M. Peters and William Bill Lorensen and David Gobbi and John Haller and Laurence Larry Clarke and Stephen Pizer and Russell H. Taylor and Robert L. Galloway, Jr. and Gabor Fichtinger and Nobuhiko Hata and Kimberly Lawson and Clare M Tempany and Ron Kikinis and Ferenc Jolesz} } @conference {Burkhardt2007, title = {A cheap and easy method for 3D C-arm reconstruction using elliptic curves}, booktitle = {Medical Imaging 2007: Visualization and Image-Guided Procedures}, volume = {6509}, number = {1}, year = {2007}, pages = {65090B}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 712395}, url = {http://link aip org/link/?PSI/6509/65090B/1}, author = {David Burkhardt and Ameet K. Jain and Gabor Fichtinger}, editor = {Kevin Cleary and Michael I. Miga} } @conference {Xu2006, title = {CT fluoroscopy-guided robotically-assisted lung biopsy}, booktitle = {Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display}, volume = {6141}, number = {1}, year = {2006}, pages = {61411L}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 652882}, url = {http://link aip org/link/?PSI/6141/61411L/1}, author = {Sheng Xu and Gabor Fichtinger and Russell H. Taylor and Filip Banovac and Kevin Cleary}, editor = {Kevin Cleary and Robert L. Galloway, Jr.} } @conference {Zhou2006, title = {Incorporating seed orientation in brachytherapy implant reconstruction}, booktitle = {Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display}, volume = {6141}, number = {1}, year = {2006}, pages = {61411H}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 654171}, url = {http://link aip org/link/?PSI/6141/61411H/1}, author = {Yu Zhou and Ameet K. Jain and Gregory Chirikjian and Gabor Fichtinger}, editor = {Kevin Cleary and Robert L. Galloway, Jr.} } @article {Xu2006a, title = {Lung deformation estimation and four-dimensional CT lung reconstruction}, journal = {Journal of Academic Radiology}, volume = {13}, number = {9}, year = {2006}, month = {Sep}, pages = {1082{\textendash}1092}, publisher = {Philips Research North America, 345 Scarborough Road, Briarcliff Manor, NY 10510, USA sheng xu@philips com}, abstract = {

RATIONALE AND OBJECTIVES: Four-dimensional (4D) computed tomography (CT) can be used in radiation treatment planning to account for respiratory motion Current 4D CT techniques have limitations in either spatial or temporal resolution In addition, most of these techniques rely on auxiliary surrogates to relate the time of the CT scan to the patient{\textquoteright}s respiratory phase We propose a 4D CT method for lung applications to overcome these problems MATERIALS AND METHODS: A set of axial scans are taken at multiple table positions to obtain a series of two-dimensional images while the patient is breathing freely Each two-dimensional image is registered to a reference CT volume The deformation of the image with respect to the volume is used to synchronize the image with the respiratory cycle assuming that there is no phase variation along the craniocaudal direction The reconstructed 4D dataset is a series of deformable transformations of the reference volume RESULTS: A synthetic 4D dataset showed that the registration error is less than 5\% of the image deformation A swine study showed that the algorithm can generate better image quality than the image sorting method A respiratory-gated 4D dataset showed that the algorithm{\textquoteright}s result is consistent with the ground truth CONCLUSION: The algorithm can reconstruct good quality 4D images without external surrogates even if the CT scans are acquired under irregular respiratory motion The algorithm may allow for reduced radiation dose to the patient with a limited loss of image quality Although the phase variation exists along the craniocaudal direction, the 4D reconstruction is reasonably accurate

}, keywords = {Algorithms, Artifacts, Computer-Assisted, Humans, Imaging, Information Storage, Lung, methods, Movement, Phantoms, Radiographic Image Enhancement, Radiographic Image Interpretation, Radiography, Reproducibility of Results, Respiratory Mechanics, Retrieval, Sensitivity, Specificity, Three-Dimensional, Tomography, X-Ray Computed}, doi = {10 1016/j acra 2006 05 004}, url = {http://dx doi org/10 1016/j acra 2006 05 004}, author = {Sheng Xu and Russell H. Taylor and Gabor Fichtinger and Kevin Cleary} } @conference {Kazanzides2006a, title = {System Architecture and Toolkits for Image-Guided Intervention Systems}, booktitle = {Medicine Meets Virtual Reality 14}, year = {2006}, author = {Peter Kazanzides and Simon DiMaio and Kevin Cleary and Gabor Fichtinger and Russell H. Taylor} } @article {Xu2005b, title = {Lung deformation estimation and four-dimensional CT lung reconstruction}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {8}, number = {Pt 2}, year = {2005}, pages = {312{\textendash}319}, abstract = {

Four-dimensional (4D) computed tomography (CT) image acquisition is a useful technique in radiation treatment planning, interventional radiology in that it can account for respiratory motion of lungs Current 4D lung reconstruction techniques have limitations in either spatial or temporal resolution In addition, most of these techniques rely on auxiliary surrogates to relate the time of CT scan to the patient{\textquoteright}s respiratory phase In this paper, we propose a novel 4D CT lung reconstruction, deformation estimation algorithm Our algorithm is purely image based The algorithm can reconstruct high quality 4D images even if the original images are acquired under irregular respiratory motion The algorithm is validated using synthetic 4D lung data Experimental results from a swine study data are also presented

}, keywords = {Algorithms, Animals, Artificial Intelligence, Biological, Computer Simulation, Computer-Assisted, Elasticity, Humans, Imaging, Lung, methods, Models, physiology/radiography, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Respiratory Mechanics, Sensitivity, Specificity, Swine, Three-Dimensional, Tomography, X-Ray Computed}, author = {Sheng Xu and Russell H. Taylor and Gabor Fichtinger and Kevin Cleary} } @article {Cleary2005, title = {Precision placement of instruments for minimally invasive procedures using a "needle driver" robot}, journal = {international journal of medical robotics computer assisted surgery MRCAS}, volume = {1}, number = {2}, year = {2005}, month = {Jan}, pages = {40{\textendash}47}, abstract = {

Medical practice continues to move toward less invasive procedures Many of these procedures require the precision placement of a needle in the anatomy Over the past several years, our research team has been investigating the use of a robotic needle driver to assist the physician in this task This paper summarizes our work in this area The robotic system is briefly described, followed by a description of a clinical trial in spinal nerve blockade The robot was used under joystick control to place a 22 gauge needle in the spines of 10 patients using fluoroscopic imaging The results were equivalent to the current manual procedure We next describe our follow-up clinical application in lung biopsy for lung cancer screening under CT fluoroscopy The system concept is discussed, the results of a phantom study are presented A start-up company named ImageGuide has recently been formed to commercialize the robot Their revised robot design is presented, along with plans to install a ceiling-mounted version of the robot in the CT fluoroscopy suite at Georgetown University

}, keywords = {Biopsy, Cadaver, Equipment Design, Fluoroscopy, Humans, Imaging, instrumentation, instrumentation/methods, Lung, Lung Neoplasms, methods, Minimally Invasive, Needles, Nerve Block, pathology, pathology/radiography, Phantoms, Randomized Controlled Trials as Topic, Robotics, Spinal Nerves, Surgical Procedures, Tomography, X-Ray Computed}, doi = {10 1002/rcs 40}, url = {http://dx doi org/10 1002/rcs 40}, author = {Kevin Cleary and Vance Watson and David Lindisch and Russell H. Taylor and Gabor Fichtinger and Sheng Xu and Charles White and John Donlon and Michael Taylor and Alexandru Patriciu and Dumitru Mazilu and Dan Stoianovici} } @conference {Xu2005a, title = {Registration and motion compensation of a needle placement robot for CT-guided spinal procedures}, booktitle = {Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display}, volume = {5744}, number = {1}, year = {2005}, pages = {661-669}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 594731}, url = {http://link aip org/link/?PSI/5744/661/1}, author = {Sheng Xu and Kevin Cleary and Dan Stoianovici and Gabor Fichtinger}, editor = {Robert L. Galloway, Jr. and Kevin Cleary} } @conference {Xu2005, title = {Validation of 3D motion tracking of pulmonary lesions using CT fluoroscopy images for robotically assisted lung biopsy}, booktitle = {Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display}, volume = {5744}, number = {1}, year = {2005}, pages = {60-68}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 594910}, url = {http://link aip org/link/?PSI/5744/60/1}, author = {Sheng Xu and Gabor Fichtinger and Russell H. Taylor and Kevin Cleary}, editor = {Robert L. Galloway, Jr. and Kevin Cleary} } @conference {Xu2004, title = {3D motion tracking of pulmonary lesions using CT fluoroscopy images for robotically assisted lung biopsy}, booktitle = {Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display}, volume = {5367}, number = {1}, year = {2004}, pages = {394-402}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 534056}, url = {http://link aip org/link/?PSI/5367/394/1}, author = {Sheng Xu and Gabor Fichtinger and Russell H. Taylor and Kevin Cleary}, editor = {Robert L. Galloway, Jr.} } @article {Cleary2004, title = {Medical Robotics workshop{\textendash}MRWS}, journal = {Journal of Computer Aided Surgery}, volume = {9}, number = {4}, year = {2004}, pages = {167{\textendash}171}, keywords = {Biomedical Research, Computer-Assisted, Humans, Operative, Robotics, Surgery, Surgical Procedures}, doi = {10 1080/10929080500097695}, url = {http://dx doi org/10 1080/10929080500097695}, author = {Kevin Cleary and Brian Davies and Gabor Fichtinger and Jocelyne Troccaz and Tim Lueth and Vance Watson} } @article {Cleary2001, title = {Automatic registration for percutaneous vertebral body tracking}, journal = {International Congress Series}, volume = {1230}, year = {2001}, pages = {1215 - 1216}, issn = {0531-5131}, doi = {DOI: 10 1016/S0531-5131(01)00045-0 }, url = {http://www sciencedirect com/science/article/B7581-47V9SDF-8B/2/b4387cef8e19f8c7dbc5d52fa97414de}, author = {Kevin Cleary and Sheng Xu and Gabor Fichtinger and Neil Glossop} }