Fast and Practical Head Tracking in Brain Imaging with Time-of-Flight Camera

Jakob Wilm, Oline Vinter Olesen, Rasmus Ramsbøl Jensen, Liselotte Højgaard, Rasmus Larsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper investigates the potential use of Time-of-Flight cameras (TOF) for motion correction in medical brain scans. TOF cameras have previously been used for tracking purposes, but recent progress in TOF technology has made it relevant for high speed optical tracking in high resolution medical scanners. Particularly in MRI and PET, the newest generation of TOF cameras could become a method of tracking small and large scale patient movement in a fast and user friendly way required in clinical environments. We present a novel methodology for fast tracking from TOF point clouds without the need of expensive triangulation and surface reconstruction. Tracking experiments with a motion controlled head phantom were performed with a translational tracking error below 2mm and a rotational tracking error below 0.5°.
Original languageEnglish
Title of host publicationProceedings of 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
Number of pages4
PublisherIEEE
Publication date2013
ISBN (Electronic)978-1-4799-0534-8
DOIs
Publication statusPublished - 2013
Event2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference and 20th Symposium on Room-Temperature: Beyond Imagination of Future Science - COEX Convention Center Grand Ball Room, Seoul, Korea, Republic of
Duration: 27 Oct 20132 Nov 2013
Conference number: 60/20
http://www.nss-mic.org/2013/nssmain.asp

Conference

Conference2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference and 20th Symposium on Room-Temperature
Number60/20
LocationCOEX Convention Center Grand Ball Room
CountryKorea, Republic of
CitySeoul
Period27/10/201302/11/2013
Internet address

Keywords

  • Nuclear Engineering
  • Biomedical imaging
  • Cameras
  • Head
  • Iterative closest point algorithm
  • Magnetic resonance imaging
  • Sensors
  • Tracking

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