Automated fiducial localization in CT images based on surface processing and geometrical prior knowledge for radiotherapy applications

IEEE Transactions on Bio-medical Engineering
Giovanni FattoriGuido Baroni

Abstract

We propose a novel method for radio-opaque external marker localization in CT scans for infrared (IR) patient set-up in radiotherapy. Efforts were focused on the quantification of uncertainties in marker localization in the CT dataset as a function of algorithm performance. We implemented a 3-D approach to fiducial localization based on surface extraction and marker recognition according to geometrical prior knowledge. The algorithm parameters were optimized on a clinical CT dataset coming from 35 cranial and extra-cranial patients; the localization accuracy was benchmarked at variable image resolution versus laser tracker measurements. The applicability of conventional IR optical tracking systems for localizing external surrogates in daily patient set-up procedures was also investigated in 121 proton therapy treatment sessions. Our study shows that the implemented algorithm features surrogates localization with uncertainties lower than 0.3 mm and with a true positive rate of 90.1%, being this latter mainly influenced by fiducial homogeneity in the CT images. The reported clinical validation in proton therapy confirmed the submillimetric accuracy and the expected algorithm sensitivity. Geometrical prior knowledge allows judging...Continue Reading

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Citations

Jul 17, 2013·Journal of Radiation Research·Maxime DesplanquesRoberto Orecchia
Dec 3, 2014·Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)·G FattoriG Baroni
Sep 2, 2016·International Journal of Computer Assisted Radiology and Surgery·Sungmin Kim, Peter Kazanzides
Sep 23, 2016·International Journal of Computer Assisted Radiology and Surgery·Hennadii MadanŽiga Špiclin
Mar 13, 2020·The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS·Abhishek KaushikGaurav Bhutani

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