@article{fichtinger2012b,

title = {Biomechanically constrained groupwise ultrasound to CT registration of the lumbar spine},

author = {Sean Gill and Purang Abolmaesumi and Gabor Fichtinger and Jonathan Boisvert and David Pichora and Dan Borshneck and Parvin Mousavi},

url = {https://www.sciencedirect.com/science/article/pii/S1361841510001003},

year  = {2012},

date = {2012-01-01},

journal = {Medical image analysis},

volume = {16},

issue = {3},

pages = {662-674},

publisher = {Elsevier},

abstract = {We present a groupwise US to CT registration algorithm for guiding percutaneous spinal interventions. In addition, we introduce a comprehensive validation scheme that accounts for changes in the curvature of the spine between preoperative and intraoperative imaging. In our registration methodology, each vertebra in CT is treated as a sub-volume and transformed individually. A biomechanical model is used to constrain the displacement of the vertebrae relative to one another. The sub-volumes are then reconstructed into a single volume. During each iteration of registration, an US image is simulated from the reconstructed CT volume and an intensity-based similarity metric is calculated with the real US image. Validation studies are performed on CT and US images from a sheep cadaver, five patient-based phantoms designed to preserve realistic curvatures of the spine and a sixth patient-based phantom where …},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{fichtinger2010g,

title = {Registration of a statistical shape model of the lumbar spine to 3D ultrasound images},

author = {Siavash Khallaghi and Parvin Mousavi and Ren Hui Gong and Sean Gill and Jonathan Boisvert and Gabor Fichtinger and David Pichora and Dan Borschneck and Purang Abolmaesumi},

url = {https://link.springer.com/chapter/10.1007/978-3-642-15745-5_9},

year  = {2010},

date = {2010-01-01},

pages = {68-75},

publisher = {Springer Berlin Heidelberg},

abstract = {Motivation: Spinal needle injections are technically demanding procedures. The use of ultrasound image guidance without prior CT and MR imagery promises to improve the efficacy and safety of these procedures in an affordable manner. Methodology: We propose to create a statistical shape model of the lumbar spine and warp this atlas to patient-specific ultrasound images during the needle placement procedure. From CT image volumes of 35 patients, statistical shape model of the L3 vertebra is built, including mean shape and main modes of variation. This shape model is registered to the ultrasound data by simultaneously optimizing the parameters of the model and its relative pose. Ground-truth data was established by printing 3D anatomical models of 3 patients using a rapid prototyping. CT and ultrasound data of these models were registered using fiducial markers. Results: Pairwise …},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{fichtinger2009g,

title = {Biomechanically constrained groupwise US to CT registration of the lumbar spine},

author = {Sean Gill and Parvin Mousavi and Gabor Fichtinger and Elvis Chen and Jonathan Boisvert and David Pichora and Purang Abolmaesumi},

url = {https://link.springer.com/chapter/10.1007/978-3-642-04268-3_99},

year  = {2009},

date = {2009-01-01},

pages = {803-810},

publisher = {Springer Berlin Heidelberg},

abstract = {Registration of intraoperative ultrasound (US) with preoperative computed tomography (CT) data for interventional guidance is a subject of immense interest, particularly for percutaneous spinal injections. We propose a biomechanically constrained group-wise registration of US to CT images of the lumbar spine. Each vertebra in CT is treated as a sub-volume and transformed individually. The sub-volumes are then reconstructed into a single volume. The algorithm simulates an US image from the CT data at each iteration of the registration. This simulated US image is used to calculate an intensity based similarity metric with the real US image. A biomechanical model is used to constrain the displacement of the vertebrae relative to one another. Covariance Matrix Adaption - Evolution Strategy (CMA-ES) is utilized as the optimization strategy. Validation is performed on CT and US images from a phantom …},

keywords = {},

pubstate = {published},

tppubtype = {article}

}