@article {Fichtinger2005,
	title = {Image overlay for CT-guided needle insertions},
	journal = {Journal of Computer Aided Surgery},
	volume = {10},
	number = {4},
	year = {2005},
	month = {Jul},
	pages = {241{\textendash}255},
	abstract = {<p>OBJECTIVE: We present a 2D image overlay device to assist needle placement on computed tomography (CT) scanners MATERIALS AND METHODS: The system consists of a flat display, a semitransparent mirror mounted on the gantry When the physician looks at the patient through the mirror, the CT image appears to be floating inside the body with correct size, position as if the physician had 2D {\textquoteright}X-ray vision{\textquoteright} The physician draws the optimal path on the CT image The composite image is rendered on the display, thus reflected in the mirror The reflected image is used to guide the physician in the procedure In this article, we describe the design, various embodiments of the 2D image overlay system, followed by the results of phantom, cadaver experiments in multiple clinical applications RESULTS: Multiple skeletal targets were successfully accessed with one insertion attempt Generally, successful access was recorded on liver targets when a clear path opened, but the number of attempts, accuracy showed variability because of occasional lack of access Soft tissue deformation further reduced the accuracy, consistency in comparison to skeletal targets CONCLUSION: The system demonstrated strong potential for reducing faulty needle insertion attempts, thereby reducing X-ray dose, patient discomfort</p>
},
	keywords = {Animals, Biopsy, Cadaver, Calibration, Computer-Assisted, Equipment Design, Humans, Image Processing, Imaging, instrumentation, Interventional, Needle, Phantoms, Radiography, Swine, Tomography, User-Computer Interface, X-Ray Computed},
	doi = {10 1080/10929080500230486},
	url = {http://dx doi org/10 1080/10929080500230486},
	author = {Gabor Fichtinger and Anton Degeut and Gregory Fischer and Iulian Iordachita and Emese Balogh and Ken Masamune and Russell H. Taylor and Laura Fayad and Michelle de Oliveira and James Zinreich}
}
@article {Xu2005b,
	title = {Lung deformation estimation and four-dimensional CT lung reconstruction},
	journal = {Medical image computing and computer-assisted intervention (MICCAI)},
	volume = {8},
	number = {Pt 2},
	year = {2005},
	pages = {312{\textendash}319},
	abstract = {<p>Four-dimensional (4D) computed tomography (CT) image acquisition is a useful technique in radiation treatment planning, interventional radiology in that it can account for respiratory motion of lungs Current 4D lung reconstruction techniques have limitations in either spatial or temporal resolution In addition, most of these techniques rely on auxiliary surrogates to relate the time of CT scan to the patient{\textquoteright}s respiratory phase In this paper, we propose a novel 4D CT lung reconstruction, deformation estimation algorithm Our algorithm is purely image based The algorithm can reconstruct high quality 4D images even if the original images are acquired under irregular respiratory motion The algorithm is validated using synthetic 4D lung data Experimental results from a swine study data are also presented</p>
},
	keywords = {Algorithms, Animals, Artificial Intelligence, Biological, Computer Simulation, Computer-Assisted, Elasticity, Humans, Imaging, Lung, methods, Models, physiology/radiography, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Respiratory Mechanics, Sensitivity, Specificity, Swine, Three-Dimensional, Tomography, X-Ray Computed},
	author = {Sheng Xu and Russell H. Taylor and Gabor Fichtinger and Kevin Cleary}
}
