Image analysis – Image enhancement or restoration – Edge or contour enhancement
Reexamination Certificate
2005-11-17
2010-02-09
Bali, Vikkram (Department: 2624)
Image analysis
Image enhancement or restoration
Edge or contour enhancement
C382S131000, C382S261000, C382S264000
Reexamination Certificate
active
07660481
ABSTRACT:
A method including receiving data corresponding to an original three-dimensional (3D) reconstructed image, smoothing homogenous areas and enhancing edges of the original reconstructed image using edge enhancing diffusion (EED) to create edge-enhanced image data, and calculating a structural importance map. The structural importance map includes a measure of structural importance for each voxel of data in the original reconstructed image. Voxel intensities to be used to create a filtered image are determined according to at least one rule applied to the measure of structural importance.
REFERENCES:
patent: 4641351 (1987-02-01), Preston, Jr.
patent: 4682291 (1987-07-01), Reuveni
patent: 5233670 (1993-08-01), Dufour et al.
patent: 5368033 (1994-11-01), Moshfeghi
patent: 5461655 (1995-10-01), Vuylsteke et al.
patent: 5533091 (1996-07-01), Hsieh
patent: 5708693 (1998-01-01), Aach et al.
patent: 5754618 (1998-05-01), Okamoto et al.
patent: 5917963 (1999-06-01), Miyake
patent: 6049623 (2000-04-01), Fuderer et al.
patent: 6173084 (2001-01-01), Aach et al.
patent: 6295331 (2001-09-01), Hsieh
patent: 6477282 (2002-11-01), Ohtsuki et al.
patent: 6493416 (2002-12-01), Hsieh
patent: 6556720 (2003-04-01), Avinash
patent: 6725174 (2004-04-01), Bouts et al.
patent: 6731821 (2004-05-01), Maurer et al.
patent: 6744532 (2004-06-01), Chen
patent: 6751286 (2004-06-01), Timmer
patent: 6775399 (2004-08-01), Jiang
patent: 6842638 (2005-01-01), Suri et al.
patent: 6873741 (2005-03-01), Li
patent: 6885762 (2005-04-01), Saha et al.
patent: 6933983 (2005-08-01), Wredenhagen et al.
patent: 7003174 (2006-02-01), Kryukov et al.
patent: 7308125 (2007-12-01), Atkinson
patent: 7352370 (2008-04-01), Wang et al.
patent: 7379561 (2008-05-01), Chauville et al.
patent: 7379626 (2008-05-01), Lachine et al.
patent: 7551795 (2009-06-01), Xu et al.
patent: 2002/0126884 (2002-09-01), Gerritsen et al.
patent: 2003/0071220 (2003-04-01), Bruder et al.
patent: 2003/0161520 (2003-08-01), Yamano et al.
patent: 2003/0223627 (2003-12-01), Yoshida et al.
patent: 2005/0002546 (2005-01-01), Florent et al.
patent: 2005/0008251 (2005-01-01), Chiang
patent: 2005/0196041 (2005-09-01), Jerebko et al.
patent: 2006/0035206 (2006-02-01), Clark et al.
patent: 2006/0045346 (2006-03-01), Zhou
patent: 1168244 (2002-01-01), None
patent: 1168244 (2004-12-01), None
patent: WO-2007061744 (2007-05-01), None
patent: WO-2007061744 (2007-05-01), None
Guido Gerig, Olaf Kubler, Ron Kikinis, and Ferenc A. Jolesz, “Nonlinear Anisotropic Filtering of MRI Data”, Jun. 1992, IEEE Transactions on Medical Imaging, vol. 11, No. 2, pp. 221-232.
“Chapter 16 Tomographic Reconstruction in Nuclear Medicine”,In: Physics in Nuclear Medicine, 3rd Edition, Cherry, S. R., et al., Editors, W. B. Saunders Company,(2003), 273-297.
“Eigenvalues Computation”, http://accad.osu.edu/˜mjiang/Projects/Eigenvalues/, 2002), 4 pgs.
“Foreword, Preface and Contents”,Spiral and Multislice Computed Tomography of the Body, Prokup, M., et al., Editors, Thieme Publishing Group,(2002), 3 pgs.
“SOMATOM Sensation Product Information”, http://www.medical.siemens.com/webapp/wcs/stores/servlet/ProductDisplay?storeId=10001&langId=-1&catalogId=-1&catTree=100001&productId=143945, (archived at archive.org on Nov. 3, 2004), 2 pgs.
Ambrose, J., “Computerized Transverse Axial Scanning (Tomography): Part 2. Clinical Application”,British Journal of Radiology, 46(542), (1973),1023-1047.
Bagnara, R., “A Unified Proof for the Convergence of Jacobi and Gauss-Seidel Methods”,Siam Review, 37(1), (1995),93-97.
Barrett, R., et al.,Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods, 2nd Edition, SIAM, Philadelphia, PA,(1994),141 pgs.
Baum, U., et al., “Verbesserung der Bildqualität in der MSCT des Beckens durch ein rohdaten-basiertes mehrdimensionales Filter / Improvement of the Image Quality of MSCT of the Pelvis With a Raw Data-Based, Multidimensional Filter”,Fortischr Rontgenstr, 175(11), (2003),1572-1576.
Boll, D. T., et al., “Assessment of Automatic Vessel Tracking Techniques in Preoperative Planning of Transluminal Aortic Stent Graft Implantation”,Journal of Computer Assisted Tomography, 28(2), (Mar./Apr. 2004), 278-285.
Catté, F. , et al., “Image Selective Smoothing and Edge Detection by Nonlinear Diffusion”,SIAM Journal on Numerical Analysis, 29(1), (1992), 182-193.
Chambolle, A., “An Algorithm for Total Variation Minimization and Applications”,Journal of Mathematical Imaging and Vision, 20, (2004), 89-97.
Chambolle, A., et al., “Image Recovery via Total Variation Minimization and Related Problems”,Numerische Mathematik, 76(2), (1997), 167-188.
Chen, Z., et al., “Breast Volume Denoising and Noise Characterization by 3D Wavelet Transform”,Computerized Medical Imaging and Graphics, 28, (2004),235-246.
Chew, E., et al., “Effect of CT Noise on Detectability of Test Objects”,American Journal of Roentgenology, 131(4), (1978), 681-685.
Depoutre, A., “The Thomas Algorithm”, http://wn7.enseeiht.fr/hmf/travaux/CD0001/travaux/optimfn/hi/01pa/hyb74
ode24.html, (2000), 3 pgs.
Dobson, D. C., et al., “Recovery of Blocky Images from Noisy and Blurred Data”,SIAM Journal on Applied Mathematics, 56(4), (1996),1181-1198.
Escalante-Ramírez, B., et al., “Multidimensional Characterization of the Perceptual Quality of Noise-Reduced Computed Tomography Images”,Journal of Visual Communication and Image Representation, 6(4), (1995), 317-334.
Frangakis, A. S., et al., “Noise Reduction in Electron Tomographic Reconstructions Using Nonlinear Anisotropic Diffusion”,Journal of Structural Biology, 135(3), (2001), 239-250.
Frangakis, A. S., et al., “Wavelet Transform Filtering and Nonlinear Anisotropic Diffusion Assessed for Signal Reconstruction Performance on Multidimensional Biomedical Data”,IEEE Transactions on Biomedical Engineering, 48(2), (2001), 213-222.
Frangi, A. F., et al., “Multiscale Vessel Enhancement Filtering”,Medical Image Computing and Computer-Assisted Intervention—MICCAI '98; Lecture Notes in Computer Science, vol. 1496, (1998),130-137.
Haaga, J. R., et al., “The Effect of mAs Variation Upon Computed Tomography Image Quality as Evaluated by In Vivo and In Vitro Studies”,Radiology, 138, (1981), 449-454.
Hanson, K. M., “Chapter 113—Noise and Contrast Discrimination in Computed Tomography”,In: Radiology of the Skull and Brain,vol. 5:Technical Aspects of Computed Tomography, Newton, T. H., et al., Editors, The C. V. Mosby Companies, St. Louis, MO, (1981), 3941-3955.
Hanson, K. M., “Detectability in Computed Tomographic Images”,Medical Physics, 6(5), (1979), 441-451.
Hilts, M. , et al., “Image Filtering for Improved Dose Resolution in CT Polymer Gel Dosimetry”,Medical Physics, 31(1), (2004), 39-49.
Hilts, M., et al., “Image Noise in X-Ray CT Polymer Gel Dosimetry”,Journal of Physics: Conference Series 3, (2004), 252-256.
Judy, P. F., et al., “Lesion Detection and Signal-to-Noise Ratio in CT Images”,Medical Physics, 8(1), (1981), 13-23.
Kalra, M. K., et al., “Can Noise Reduction Filters Improve Low-Radiation-Dose Chest CT Images? Pilot Study”,Radiology, 228(1), (2003),251-256.
Kalra, M. K., et al., “Low-Dose CT of the Abdomen: Evaluation of Image Improvement With Use of Noise Reduction Filters—Pilot Study”,Radiology, 228(1), (2003), 251-256.
Keselbrener, L., et al., “Nonlinear Filters Applied On Computerized Axial Tomography: Theory and Phantom Images”,Medical Physics, 19(4), (Jul./Aug. 1992), 1057-1064.
Ko, J. P., et al., “Wavelet Compression of Low-Dose Chest CT Data: Effect on Lung Nodule Detection”,Radiology, 228(1), (2003), 70-75.
Koenderink, J. J., “The Structure of Images”,Biological Cybernetics, 5
Schaap Michiel
Zuiderveld Karel
Bali Vikkram
Entezari Michelle
Schwegman Lundberg & Woessner, P.A.
Vital Images, Inc.
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