TY - JOUR
T1 - Increasing the impact of medical image computing using community-based open-access hackathons
T2 - The NA-MIC and 3D Slicer experience
AU - Kapur, Tina
AU - Pieper, Steve
AU - Fedorov, Andriy
AU - Fillion-Robin, J. C.
AU - Halle, Michael
AU - O'Donnell, Lauren
AU - Lasso, Andras
AU - Ungi, Tamas
AU - Pinter, Csaba
AU - Finet, Julien
AU - Pujol, Sonia
AU - Jagadeesan, Jayender
AU - Tokuda, Junichi
AU - Norton, Isaiah
AU - Estepar, Raul San Jose
AU - Gering, David
AU - Aerts, Hugo J W L
AU - Jakab, Marianna
AU - Hata, Nobuhiko
AU - Ibanez, Luiz
AU - Blezek, Daniel
AU - Miller, Jim
AU - Aylward, Stephen
AU - Grimson, W. Eric L
AU - Fichtinger, Gabor
AU - Wells, William M.
AU - Lorensen, William E.
AU - Schroeder, Will
AU - Kikinis, Ron
PY - 2016/10/1
Y1 - 2016/10/1
N2 - 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—VTK, ITK, CMake, CDash, DCMTK—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 (“Open Science”); 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.
AB - 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—VTK, ITK, CMake, CDash, DCMTK—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 (“Open Science”); 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.
KW - 3D Slicer
KW - Hackathon
KW - Medical image computing
KW - NA-MIC
KW - Open access
KW - Open science
KW - Open source
KW - Project week
KW - Reproducible research
UR - http://www.scopus.com/inward/record.url?scp=84982182311&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84982182311&partnerID=8YFLogxK
U2 - 10.1016/j.media.2016.06.035
DO - 10.1016/j.media.2016.06.035
M3 - Editorial
C2 - 27498015
AN - SCOPUS:84982182311
SN - 1361-8415
VL - 33
SP - 176
EP - 180
JO - Medical Image Analysis
JF - Medical Image Analysis
ER -