PURPOSE: Navigation systems commonly used in neurosurgery suffer from two main drawbacks: (1) their accuracy degrades over the course of the operation and (2) they require the surgeon to mentally map images from the monitor to the patient. In this paper, we introduce the Intraoperative Brain Imaging System (IBIS), an open-source image-guided neurosurgery research platform that implements a novel workflow where navigation accuracy is improved using tracked intraoperative ultrasound (iUS) and the visualization of navigation information is facilitated through the use of augmented reality (AR). METHODS: The IBIS platform allows a surgeon to capture tracked iUS images and use them to automatically update preoperative patient models and plans through fast GPU-based reconstruction and registration methods. Navigation, resection and iUS-based brain shift correction can all be performed using an AR view. IBIS has an intuitive graphical user interface for the calibration of a US probe, a surgical pointer as well as video devices used for AR (e.g., a surgical microscope). RESULTS: The components of IBIS have been validated in the laboratory and evaluated in the operating room. Image-to-patient registration accuracy is on the order of [Formula: see text] and can be improved with iUS to a median target registration error of 2.54 mm. The accuracy of the US probe calibration is between 0.49 and 0.82 mm. The average reprojection error of the AR system is [Formula: see text]. The system has been used in the operating room for various types of surgery, including brain tumor resection, vascular neurosurgery, spine surgery and DBS electrode implantation. CONCLUSIONS: The IBIS platform is a validated system that allows researchers to quickly bring the results of their work into the operating room for evaluation. It is the first open-source navigation system to provide a complete solution for AR visualization.
PURPOSE: Navigation systems commonly used in neurosurgery suffer from two main drawbacks: (1) their accuracy degrades over the course of the operation and (2) they require the surgeon to mentally map images from the monitor to the patient. In this paper, we introduce the Intraoperative Brain Imaging System (IBIS), an open-source image-guided neurosurgery research platform that implements a novel workflow where navigation accuracy is improved using tracked intraoperative ultrasound (iUS) and the visualization of navigation information is facilitated through the use of augmented reality (AR). METHODS: The IBIS platform allows a surgeon to capture tracked iUS images and use them to automatically update preoperative patient models and plans through fast GPU-based reconstruction and registration methods. Navigation, resection and iUS-based brain shift correction can all be performed using an AR view. IBIS has an intuitive graphical user interface for the calibration of a US probe, a surgical pointer as well as video devices used for AR (e.g., a surgical microscope). RESULTS: The components of IBIS have been validated in the laboratory and evaluated in the operating room. Image-to-patient registration accuracy is on the order of [Formula: see text] and can be improved with iUS to a median target registration error of 2.54 mm. The accuracy of the US probe calibration is between 0.49 and 0.82 mm. The average reprojection error of the AR system is [Formula: see text]. The system has been used in the operating room for various types of surgery, including brain tumor resection, vascular neurosurgery, spine surgery and DBS electrode implantation. CONCLUSIONS: The IBIS platform is a validated system that allows researchers to quickly bring the results of their work into the operating room for evaluation. It is the first open-source navigation system to provide a complete solution for AR visualization.
Authors: Charles X B Yan; Benoît Goulet; Donatella Tampieri; D Louis Collins Journal: Int J Comput Assist Radiol Surg Date: 2012-06-15 Impact factor: 2.924
Authors: Laurence Mercier; Rolando F Del Maestro; Kevin Petrecca; Anna Kochanowska; Simon Drouin; Charles X B Yan; Andrew L Janke; Sean Jy-Shyang Chen; D Louis Collins Journal: Int J Comput Assist Radiol Surg Date: 2010-10-01 Impact factor: 2.924
Authors: R Zelmann; S Beriault; M M Marinho; K Mok; J A Hall; N Guizard; C Haegelen; A Olivier; G B Pike; D L Collins Journal: Int J Comput Assist Radiol Surg Date: 2015-03-26 Impact factor: 2.924
Authors: Marta Kersten-Oertel; Ian Gerard; Simon Drouin; Kelvin Mok; Denis Sirhan; David S Sinclair; D Louis Collins Journal: Int J Comput Assist Radiol Surg Date: 2015-02-26 Impact factor: 2.924
Authors: Andinet Enquobahrie; Patrick Cheng; Kevin Gary; Luis Ibanez; David Gobbi; Frank Lindseth; Ziv Yaniv; Stephen Aylward; Julien Jomier; Kevin Cleary Journal: J Digit Imaging Date: 2007-08-17 Impact factor: 4.056
Authors: Maxime Chamberland; Michaël Bernier; David Fortin; Kevin Whittingstall; Maxime Descoteaux Journal: Front Neurosci Date: 2015-08-11 Impact factor: 4.677
Authors: Christian Askeland; Ole Vegard Solberg; Janne Beate Lervik Bakeng; Ingerid Reinertsen; Geir Arne Tangen; Erlend Fagertun Hofstad; Daniel Høyer Iversen; Cecilie Våpenstad; Tormod Selbekk; Thomas Langø; Toril A Nagelhus Hernes; Håkon Olav Leira; Geirmund Unsgård; Frank Lindseth Journal: Int J Comput Assist Radiol Surg Date: 2015-09-26 Impact factor: 2.924
Authors: Sarah Frisken; Ma Luo; Parikshit Juvekar; Adomas Bunevicius; Ines Machado; Prashin Unadkat; Melina M Bertotti; Matt Toews; William M Wells; Michael I Miga; Alexandra J Golby Journal: Int J Comput Assist Radiol Surg Date: 2019-08-23 Impact factor: 2.924
Authors: Houssem-Eddine Gueziri; Simon Drouin; Charles X B Yan; D Louis Collins Journal: Int J Comput Assist Radiol Surg Date: 2019-06-28 Impact factor: 2.924
Authors: Pedro Aguilar-Salinas; Salvador F Gutierrez-Aguirre; Mauricio J Avila; Peter Nakaji Journal: Neurosurg Rev Date: 2022-02-11 Impact factor: 3.042
Authors: Ian J Gerard; Marta Kersten-Oertel; Simon Drouin; Jeffery A Hall; Kevin Petrecca; Dante De Nigris; Daniel A Di Giovanni; Tal Arbel; D Louis Collins Journal: J Med Imaging (Bellingham) Date: 2018-01-26