@article {Kapur2016, title = {Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience}, journal = {Medical Image Analysis}, volume = {33}, year = {2016}, month = {10/2016}, pages = {176-180}, abstract = {

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools{\textemdash}VTK, ITK, CMake, CDash, DCMTK{\textemdash}were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ({\textquotedblleft}Open Science{\textquotedblright}); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision.

}, keywords = {3D Slicer, Hackathon, Medical image computing, NA-MIC, Open access, Open science, Open source, Project week, Reproducible research}, doi = {http://doi.org/10.1016/j.media.2016.06.035}, author = {Tina Kapur and Steve Pieper and Andras Lasso and Tamas Ungi and Csaba Pinter and Gabor Fichtinger and Ron Kikinis} } @conference {King2015, title = {An Immersive Virtual Reality Environment for Diagnostic Imaging}, booktitle = {Int Conf Med Image Comput Comput Assist Interv. MICCAI 2015}, year = {2015}, month = {10/2015}, abstract = {

Advancements in and adoption of consumer virtual reality are currently being propelled by numerous upcoming devices such as the Oculus Rift. Although applications are currently growing around the entertainment field, widespread adoption of virtual reality devices opens up the potential for other applications that may have been unfeasible with past implementations of virtual reality. A virtual reality environment may provide an equal or larger viewing volume than what is provided with the use of multiple conventional displays while remaining comparatively cheaper and more portable. A virtual reality application for the viewing of multiple image slices was designed using: the Oculus Rift head-mounted display, Unity, 3D Slicer, and a gamepad controller. A web server acquires data from volumes loaded within 3D Slicer and forwards it to a Unity application that proceeds to render a scene for the Oculus Rift head- mounted display. Users may interact with the images adjusting windowing and leveling using the handheld gamepad controller. Multiple images could also be brought closer to the user for detailed inspection. Application usage was demonstrated with the simultaneous visualization of concurrent slices of a serial CT scan of a patient with a lung nodule. The tasks of identifying the lesion and determining the malignancy status by monitoring the growth of the lesion over time were performed successfully. Also demonstrated was the studying of multiple- sclerosis lesion evolution by visualization of a large time-series MRI dataset. A virtual reality environment for the purpose of aiding diagnostic radiology has been created and demonstrated with potential use cases.

}, author = {Franklin King and Jagadeesan Jayender and Steve Pieper and Tina Kapur and Andras Lasso and Gabor Fichtinger} } @article {raey, title = {Open-source image registration for MRI-TRUS fusion-guided prostate interventions}, journal = {International Journal of Computer Assisted Radiology and Surgery}, volume = {10}, number = {6}, year = {2015}, pages = {925-934}, keywords = {Image registration, Image-guided interventions, Magnetic Resonance Imaging, prostate cancer, Targeted biopsy, Ultrasound}, issn = {1861-6410}, doi = {10.1007/s11548-015-1180-7}, url = {http://dx.doi.org/10.1007/s11548-015-1180-7}, author = {Andriy Fedorov and Siavash Khallaghi and Sanchez, C. Antonio and Andras Lasso and Fels, Sidney and Kemal Tuncali and Sugar, Emily Neubauer and Tina Kapur and Zhang, Chenxi and William Wells and Paul Nguyen and Purang Abolmaesumi and Clare M Tempany} } @article {Fedorov2013, title = {Towards Open Source Infrastructure for Joint MRI/TRUS Guided Prostate Interventions}, volume = {6}, year = {2013}, month = {03/2013}, pages = {67}, address = {Crystal City, VA, USA}, url = {http://www.spl.harvard.edu/publications/item/view/2334}, author = {Andriy Fedorov and Andras Lasso and Mehdi Moradi and Sang-Eun Song and Emily Neubauer and Robert Owen and Tina Kapur and William Wells and Paul Nguyen and Gabor Fichtinger and Clare M Tempany} } @conference {Tokuda2009, title = {OpenIGTLink: An Open Network Protocol for Image Guided Therapy Environment}, booktitle = {International Journal of Medical Robotics and Computer Assisted Surgery}, volume = {na}, year = {2009}, pages = {na}, author = {Junichi Tokuda and Luis Ibanez and Gregory Fischer and Patrick Cheng and Haiying Liu and Jack Blevins and Jumpei Arata and Xenophon Papademetris and Ziv Yaniv and Tina Kapur and Steve Pieper and E. Clif Burdette and Gabor Fichtinger and Clare M Tempany and Nobuhiko Hata} } @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} }