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543 results on '"Fichtinger G"'

4. Dynamic MRI Scan Plane Control for Passive Tracking of Instruments and Devices

Author

DiMaio, S. P., Samset, E., Fischer, G., Iordachita, I., Fichtinger, G., Jolesz, F., Tempany, C. M., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ayache, Nicholas, editor, Ourselin, Sébastien, editor, and Maeder, Anthony, editor

Published
2007
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5. Intra-operative 3D Guidance in Prostate Brachytherapy Using a Non-isocentric C-arm

Author

Jain, A., Deguet, A., Iordachita, I., Chintalapani, G., Blevins, J., Le, Y., Armour, E., Burdette, C., Song, D., Fichtinger, G., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ayache, Nicholas, editor, Ourselin, Sébastien, editor, and Maeder, Anthony, editor

Published
2007
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32. Model-updated image-guided minimally invasive off-pump transcatheter aortic valve implantation

Author

Fichtinger, G, Martel, A, Peters, T, Fichtinger, G ( G ), Martel, A ( A ), Peters, T ( T ), Karar, M E, John, M, Holzhey, D, Falk, V, Mohr, F W, Burgert, O, Fichtinger, G, Martel, A, Peters, T, Fichtinger, G ( G ), Martel, A ( A ), Peters, T ( T ), Karar, M E, John, M, Holzhey, D, Falk, V, Mohr, F W, and Burgert, O

Abstract

This paper presents a method for assisting the placement of stented aortic valve prosthesis during minimally invasive off-pump transcatheter aortic valve implantation (TAVI) under live 2-D X-ray fluoroscopy guidance. The proposed method includes a dynamic overlay of an intra-operative 3-D aortic root mesh model and an estimated target area of valve implantation onto live 2-D fluoroscopic images. This is based on a template-based tracking procedure of a pigtail catheter without further injections of contrast agent. Minimal user-interaction is required to initialize the algorithm and to correct fluoroscopy overlay errors if needed. Retrospective experiments were carried out on ten patient datasets from the clinical routine of the TAVI. The mean displacement errors of the updated aortic root mesh model overlays are less than 2.0 mm without manual overlay corrections. The results show that the guidance performance of live 2-D fluoroscopy is potentially improved when using our proposed method for the TAVIs.

Published
2011

35. Visual feedback mounted on surgical tool: proof of concept

Author

Carter, K., additional, Vaughan, T., additional, Holden, M., additional, Gauvin, G., additional, Pezeshki, P., additional, Lasso, A., additional, Ungi, T., additional, Morin, E., additional, Rudan, J., additional, Engel, C. J., additional, and Fichtinger, G., additional

Published
2016
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40. Preconditioned stochastic gradient descent optimisation for monomodal image registration

Author

Klein, S., Staring, M., Andersson, J.P., Pluim, J.P.W., Fichtinger, G., Martel, A., Peters, T., and Medical Image Analysis

Subjects
Hessian matrix, business.industry, Preconditioner, Stochastic process, Physics::Medical Physics, Image registration, Image processing, symbols.namesake, Stochastic gradient descent, Rate of convergence, Computer Science::Computer Vision and Pattern Recognition, symbols, Computer vision, Artificial intelligence, Gradient descent, business, Algorithm, Mathematics
Abstract

We present a stochastic optimisation method for intensity-based monomodal image registration. The method is based on a Robbins-Monro stochastic gradient descent method with adaptive step size estimation, and adds a preconditioning matrix. The derivation of the pre-conditioner is based on the observation that, after registration, the deformed moving image should approximately equal the fixed image. This prior knowledge allows us to approximate the Hessian at the minimum of the registration cost function, without knowing the coordinate transformation that corresponds to this minimum. The method is validated on 3D fMRI time-series and 3D CT chest follow-up scans. The experimental results show that the preconditioning strategy improves the rate of convergence.

Published
2011

45. Rigid motion compensation with a robotized 2D ultrasound probe using speckle information and visual servoing

Author

Alexandre Krupa, Fichtinger, G., Hager, G. D., Visual servoing in robotics, computer vision, and augmented reality (Lagadic), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Johns Hopkins University (JHU), Yale University [New Haven], Burschka, D. and Hager, G.D. and Konietschke, R. and Okamura, A.M., Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2009

47. Semi-automatic reference standard construction for quantitative evaluation of lung CT registration

Author

Murphy, K., Ginneken, van, B., Pluim, J.P.W., Klein, S., Staring, M., Metzaxas, D., Axel, L., Fichtinger, G., Székely, G., and Medical Image Analysis

Subjects
Set (abstract data type), Matching (graph theory), medicine.diagnostic_test, Computer science, business.industry, Interface (computing), medicine, Computer vision, Computed tomography, Semi automatic, Artificial intelligence, business, Reference standards
Abstract

An algorithm is presented for the efficient semi-automatic construction of a detailed reference standard for registration in thoracic CT. A well-distributed set of 100 landmarks is detected fully automatically in one scan of a pair to be registered. Using a custom-designed interface, observers locate corresponding anatomic locations in the second scan. The manual annotations are used to learn the relationship between the scans and after approximately twenty manual marks the remaining points are matched automatically. Inter-observer differences demonstrate the accuracy of the matching and the applicability of the reference standard is demonstrated on two different sets of registration results over 19 CT scan pairs. © 2008 Springer Berlin Heidelberg.

Published
2008

48. Optimal Acquisition Schemes in High Angular Resolution Diffusion Weighted Imaging

Author

Prčkovska, Vesna, Roebroeck, Alard F., Pullens, W.L.P.M., Vilanova, Anna, ter Haar Romeny, Bart M., Metaxas, D., Axel, L., Fichtinger, G., Székely, G., Medical Image Analysis, Visualization, Cognitive Neuroscience, and Beeldvorming

Subjects
Myelinated/ultrastructure, Sensitivity and Specificity, Regularization (mathematics), Nerve Fibers, Neuroimaging, Computer-Assisted/methods, Humans, Angular resolution, Computer vision, Brain/anatomy & histology, Diffusion (business), Image Interpretation, Mathematics, Information Storage and Retrieval/methods, Orientation (computer vision), business.industry, Image Interpretation, Computer-Assisted/methods, Work (physics), Reproducibility of Results, Diffusion Magnetic Resonance Imaging/methods, Artificial intelligence, Noise (video), Image Enhancement/methods, Nerve Fibers, Myelinated/ultrastructure, business, Algorithm, Algorithms, Diffusion MRI
Abstract

The recent challenge in diffusion imaging is to find acquisition schemes and analysis approaches that can represent non-gaussian diffusion profiles in a clinically feasible measurement time. In this work we investigate the effect of b-value and the number of gradient vector directions on Q-ball imaging and the Diffusion Orientation Transform (DOT) in a structured way using computational simulations, hardware crossing-fiber diffusion phantoms, and in-vivo brain scans. We observe that DOT is more robust to noise and independent of the b-value and number of gradients, whereas Q-ball dramatically improves the results for higher b-values and number of gradients and at recovering larger angles of crossing. We also show that Laplace-Beltrami regularization has wide applicability and generally improves the properties of DOT. Knowledge of optimal acquisition schemes for HARDI can improve the utility of diffusion weighted MR imaging in the clinical setting for the diagnosis of white matter diseases and presurgical planning.

Published
2008

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