@article {DiMaio2007,
	title = {Dynamic MRI scan plane control for passive tracking of instruments and devices},
	journal = {Medical image computing and computer-assisted intervention (MICCAI)},
	volume = {10},
	number = {Pt 2},
	year = {2007},
	pages = {50{\textendash}58},
	publisher = {Brigham, Women{\textquoteright}s Hospital, Harvard Medical School, Boston, MA, USA},
	abstract = {<p>This paper describes a novel image-based method for tracking robotic mechanisms, interventional devices during Magnetic Resonance Image (MRI)-guided procedures It takes advantage of the multi-planar imaging capabilities of MRI to optimally image a set of localizing fiducials for passive motion tracking in the image coordinate frame The imaging system is servoed to adaptively position the scan plane based on automatic detection, localization of fiducial artifacts directly from the acquired image stream This closed-loop control system has been implemented using an open-source software framework, currently operates with GE MRI scanners Accuracy, performance were evaluated in experiments, the results of which are presented here</p>
},
	keywords = {Algorithms, Anatomy, Artificial Intelligence, Automated, Computer-Assisted, Cross-Sectional, Humans, Image Enhancement, Image Interpretation, Imaging, instrumentation/methods, Magnetic Resonance Imaging, methods, Pattern Recognition, Phantoms, Reproducibility of Results, Robotics, Sensitivity, Specificity, Surgery, Three-Dimensional, User-Computer Interface},
	author = {Simon DiMaio and Eigil Samset and Gregory Fischer and Iulian Iordachita and Gabor Fichtinger and Ferenc Jolesz and Clare M Tempany}
}
@article {DiMaio2006,
	title = {Needle artifact localization in 3T MR images},
	journal = {Studies in health technology and informatics},
	volume = {119},
	year = {2006},
	pages = {120{\textendash}125},
	publisher = {Brigham, Women{\textquoteright}s Hospital, Harvard Medical School, Boston 02115, USA simond@bwh harvard edu},
	abstract = {<p>This work explores an image-based approach for localizing needles during MRI-guided interventions, for the purpose of tracking, navigation Susceptibility artifacts for several needles of varying thickness were imaged, in phantoms, using a 3 tesla MRI system, under a variety of conditions The relationship between the true needle positions, the locations of artifacts within the images, determined both by manual, automatic segmentation methods, have been quantified, are presented here</p>
},
	keywords = {Artifacts, Magnetic Resonance Imaging, Needles, United States},
	author = {Simon DiMaio and Daniel Kacher and Randy Ellis and Gabor Fichtinger and Nobuhiko Hata and Gary Zientara and Lawrence Panych and Ron Kikinis and Ferenc Jolesz}
}
