Level-set algorithm for the reconstruction of functional activation in near-infrared spectroscopic imaging.
暂无分享,去创建一个
Yoram Bresler | Vlad Toronov | Xiaofeng Zhang | Mathews Jacob | Andrew Webb | Y. Bresler | A. Webb | M. Jacob | V. Toronov | Xiaofeng Zhang
[1] Emmanuel Candes,et al. Stable signal recovery from incomplete observations , 2005, SPIE Optics + Photonics.
[2] G. Sapiro,et al. Geometric partial differential equations and image analysis [Book Reviews] , 2001, IEEE Transactions on Medical Imaging.
[3] Demetri Terzopoulos,et al. Snakes: Active contour models , 2004, International Journal of Computer Vision.
[4] R. J. Gaudette,et al. A comparison study of linear reconstruction techniques for diffuse optical tomographic imaging of absorption coefficient. , 2000, Physics in medicine and biology.
[5] Mario Bertero,et al. Introduction to Inverse Problems in Imaging , 1998 .
[6] Yao Wang,et al. A wavelet-based multiresolution regularized least squares reconstruction approach for optical tomography , 1997, IEEE Transactions on Medical Imaging.
[7] Vladislav Toronov,et al. Simultaneous integrated diffuse optical tomography and functional magnetic resonance imaging of the human brain. , 2005, Optics express.
[8] Y. Bresler,et al. Spectrum-blind minimum-rate sampling and reconstruction of 2-D multiband signals , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.
[9] W. Clem Karl,et al. A curve evolution approach to object-based tomographic reconstruction , 2003, IEEE Trans. Image Process..
[10] Baba C. Vemuri,et al. Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[11] James G. Fujimoto,et al. Dispersion-managed mode locking , 1999 .
[12] D. Boas,et al. Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. , 2002, Optics express.
[13] D. Donoho. For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solution , 2006 .
[14] Wolfgang Osten,et al. Introduction to Inverse Problems in Imaging , 1999 .
[15] Pierre Moulin,et al. A Self-Referencing Level-Set Method for Image Reconstruction from Sparse Fourier Samples , 2004, International Journal of Computer Vision.
[16] D. Hood,et al. Fast and Localized Event-Related Optical Signals (EROS) in the Human Occipital Cortex: Comparisons with the Visual Evoked Potential and fMRI , 1997, NeuroImage.
[17] Anders M. Dale,et al. Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy , 2004, NeuroImage.
[18] Thierry Blu,et al. Efficient energies and algorithms for parametric snakes , 2004, IEEE Transactions on Image Processing.
[19] David Boas,et al. Three-dimensional shape-based imaging of absorption perturbation for diffuse optical tomography. , 2003, Applied optics.
[20] D. Delpy,et al. Optical Imaging in Medicine , 1998, CLEO/Europe Conference on Lasers and Electro-Optics.
[21] W. Clem Karl,et al. Dynamic tomography using curve evolution with spatial-temporal regularization , 2002, Proceedings. International Conference on Image Processing.
[22] Nick Everdell,et al. Optical tomography of the breast using a multi-channel time-resolved imager , 2005, Physics in medicine and biology.
[23] A. Dale,et al. Robust inference of baseline optical properties of the human head with three-dimensional segmentation from magnetic resonance imaging. , 2003, Applied optics.
[24] J. Zolésio,et al. Introduction to shape optimization : shape sensitivity analysis , 1992 .
[25] Yoram Bresler,et al. Further results on spectrum blind sampling of 2D signals , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).
[26] S. Arridge. Optical tomography in medical imaging , 1999 .
[27] R. Cubeddu,et al. Optical Tomography , 1998, Technical Digest. 1998 EQEC. European Quantum Electronics Conference (Cat. No.98TH8326).
[28] Charles L. Matson,et al. Backpropagation in turbid media , 1999 .
[29] Olivier Faugeras,et al. Reconciling Distance Functions and Level Sets , 2000, J. Vis. Commun. Image Represent..
[30] C VemuriBaba,et al. Shape Modeling with Front Propagation , 1995 .
[31] S. Arridge,et al. Optical imaging in medicine: II. Modelling and reconstruction , 1997, Physics in medicine and biology.
[32] E. Okada,et al. Monte Carlo prediction of near-infrared light propagation in realistic adult and neonatal head models. , 2003, Applied optics.
[33] D. Mumford,et al. Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .
[34] E. Gratton,et al. Measurement of brain activity by near-infrared light. , 2005, Journal of biomedical optics.
[35] Ping Feng,et al. Spectrum-blind minimum-rate sampling and reconstruction of multiband signals , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.
[36] E. Miller,et al. Optimal linear inverse solution with multiple priors in diffuse optical tomography. , 2005, Applied optics.
[37] A Villringer,et al. Cerebral blood oxygenation changes induced by visual stimulation in humans. , 1996, Journal of biomedical optics.
[38] E. Candès,et al. Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.
[39] C H Schmitz,et al. Optical tomographic imaging of dynamic features of dense-scattering media. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.
[40] E Gratton,et al. Propagation of photon-density waves in strongly scattering media containing an absorbing semi-infinite plane bounded by a straight edge. , 1993, Journal of the Optical Society of America. A, Optics and image science.
[41] David A Boas,et al. Simulation study of magnetic resonance imaging-guided cortically constrained diffuse optical tomography of human brain function. , 2005, Applied optics.
[42] D. Boas,et al. Experimental images of heterogeneous turbid media by frequency-domain diffusing-photon tomography. , 1995, Optics letters.
[43] B. Pogue,et al. Spatially variant regularization improves diffuse optical tomography. , 1999, Applied optics.
[44] J. Sethian,et al. Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .
[45] Anthony J. Yezzi,et al. Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification , 2001, IEEE Trans. Image Process..
[46] C L Matson,et al. Three-dimensional tumor localization in thick tissue with the use of diffuse photon-density waves. , 1997, Applied optics.
[47] F. Santosa. A Level-set Approach Inverse Problems Involving Obstacles , 1995 .
[48] Alexander D. Klose,et al. Gradient-based iterative image reconstruction scheme for time-resolved optical tomography , 1999, IEEE Transactions on Medical Imaging.