@conference {Anand2014b, title = {Design and Development of a Mobile Image Overlay System for Image-Guided Needle Interventions}, booktitle = {36th Annual International Conference of IEEE EMBS}, year = {2014}, month = {Accepted}, publisher = {IEEE EMBS}, organization = {IEEE EMBS}, address = {Chicago, IL, USA}, author = {Manjunath Anand and Franklin King and Tamas Ungi and Andras Lasso and John Rudan and Jagadeesan Jayender and Jan Fritz and John A Carrino and Ferenc Jolesz and Gabor Fichtinger} } @article {Anand2014a, title = {Design of mobile image overlay system for image-guided interventions}, year = {2014}, month = {03/2014}, publisher = {ImNO}, address = {Toronto, Canada. March 24-25}, author = {Manjunath Anand and Franklin King and Tamas Ungi and Andras Lasso and John Rudan and Jagadeesan Jayender and Jan Fritz and Ferenc Jolesz and John A Carrino and Gabor Fichtinger} } @article {Anand2013a, title = {Mobile Image Overlay System for Image Guided Interventions}, year = {2013}, month = {03/2013}, address = {Washington DC, USA, March 21-23, 2013.}, keywords = {image guided interventions, mobile image overlay, needle placement interventions, percutaneous interventions, static image overlay}, author = {Manjunath Anand and Tamas Ungi and Andras Lasso and Paweena U-Thainual and Jagadeesan Jayender and Jan Fritz and John A Carrino and Ferenc Jolesz and Gabor Fichtinger} } @article {Anand2013c, title = {MOBILE IMAGE OVERLAY SYSTEM (MIOS) FOR IMAGE GUIDED INTERVENTIONS}, year = {2013}, month = {06/2013}, address = {Faculty of Health Sciences, Queen{\textquoteright}s University}, author = {Manjunath Anand and Tamas Ungi and Andras Lasso and Paweena U-Thainual and Jagadeesan Jayender and Jan Fritz and John A Carrino and Ferenc Jolesz and Gabor Fichtinger} } @conference {Anand2013b, title = {Workspace Analysis and Calibration Method for Mobile Image Overlay System used for Image-Guided Interventions}, booktitle = {The Hamlyn Symposium on Medical Robotics - 2013}, year = {2013}, month = {06/2013}, author = {Manjunath Anand and Tamas Ungi and Andras Lasso and Paweena U-Thainual and Jagadeesan Jayender and Jan Fritz and John A Carrino and Ferenc Jolesz and Gabor Fichtinger} } @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} } @article {DiMaio2007, title = {Dynamic MRI scan plane control for passive tracking of instruments and devices}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {10}, number = {Pt 2}, year = {2007}, pages = {50{\textendash}58}, publisher = {Brigham, Women{\textquoteright}s Hospital, Harvard Medical School, Boston, MA, USA}, abstract = {

This paper describes a novel image-based method for tracking robotic mechanisms, interventional devices during Magnetic Resonance Image (MRI)-guided procedures It takes advantage of the multi-planar imaging capabilities of MRI to optimally image a set of localizing fiducials for passive motion tracking in the image coordinate frame The imaging system is servoed to adaptively position the scan plane based on automatic detection, localization of fiducial artifacts directly from the acquired image stream This closed-loop control system has been implemented using an open-source software framework, currently operates with GE MRI scanners Accuracy, performance were evaluated in experiments, the results of which are presented here

}, keywords = {Algorithms, Anatomy, Artificial Intelligence, Automated, Computer-Assisted, Cross-Sectional, Humans, Image Enhancement, Image Interpretation, Imaging, instrumentation/methods, Magnetic Resonance Imaging, methods, Pattern Recognition, Phantoms, Reproducibility of Results, Robotics, Sensitivity, Specificity, Surgery, Three-Dimensional, User-Computer Interface}, author = {Simon DiMaio and Eigil Samset and Gregory Fischer and Iulian Iordachita and Gabor Fichtinger and Ferenc Jolesz and Clare M Tempany} } @article {DiMaio2006, title = {Needle artifact localization in 3T MR images}, journal = {Studies in health technology and informatics}, volume = {119}, year = {2006}, pages = {120{\textendash}125}, publisher = {Brigham, Women{\textquoteright}s Hospital, Harvard Medical School, Boston 02115, USA simond@bwh harvard edu}, abstract = {

This work explores an image-based approach for localizing needles during MRI-guided interventions, for the purpose of tracking, navigation Susceptibility artifacts for several needles of varying thickness were imaged, in phantoms, using a 3 tesla MRI system, under a variety of conditions The relationship between the true needle positions, the locations of artifacts within the images, determined both by manual, automatic segmentation methods, have been quantified, are presented here

}, keywords = {Artifacts, Magnetic Resonance Imaging, Needles, United States}, author = {Simon DiMaio and Daniel Kacher and Randy Ellis and Gabor Fichtinger and Nobuhiko Hata and Gary Zientara and Lawrence Panych and Ron Kikinis and Ferenc Jolesz} }