Artificial Intelligence and Signal Processing

This paper proposes a grouping based technique of multivariate analysis, and it is extended to nonlinear kernel based version for hyperspectral image classification. Grouped multivariate analysis methods are presented in the Euclidean space and dot products are replaced by kernels in Hilbert space for nonlinear dimension reduction and data visualization. We show that the proposed kernel analysis method greatly enhances the classification performance. Experiments on Classification are presented based on Indian Pine real dataset collected from the 224-dimensional AVIRIS hyperspectral sensor, and the performance of proposed approach is investigated. Results show that the Kernel Grouped Multivariate discriminant Analysis (KGMVA) method is generally efficient to improve overall accuracy.

[1]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  David G. Stork,et al.  Pattern Classification (2nd ed.) , 1999 .

[3]  A S Frangakis,et al.  Noise reduction in electron tomographic reconstructions using nonlinear anisotropic diffusion. , 2001, Journal of structural biology.

[4]  Hanno Scharr,et al.  A Scheme for Coherence-Enhancing Diffusion Filtering with Optimized Rotation Invariance , 2002, J. Vis. Commun. Image Represent..

[5]  Weiguang Guan,et al.  Automatic needle segmentation in 3D ultrasound images , 2002, SPIE Medical Imaging.

[6]  Robert D. Howe,et al.  Tool Localization in 3D Ultrasound Images , 2003, MICCAI.

[7]  Aaron Fenster,et al.  Automatic needle segmentation in three-dimensional ultrasound images using two orthogonal two-dimensional image projections. , 2003, Medical physics.

[8]  Gavin C. Cawley,et al.  Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers , 2003, Pattern Recognit..

[9]  D. Downey,et al.  Oblique needle segmentation for 3D TRUS-guided robot-aided transperineal prostate brachytherapy , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[10]  Chih-Jen Lin,et al.  A tutorial on?-support vector machines , 2005 .

[11]  L. Fritz.  Diffusion-Based Applications for Interactive Medical Image Segmentation , 2006 .

[12]  Robert D. Howe,et al.  GPU based real-time instrument tracking with three-dimensional ultrasound , 2007, Medical Image Anal..

[13]  Mingyue Ding,et al.  Needle Segmentation Using 3D Quick Randomized Hough Transform , 2008, 2008 First International Conference on Intelligent Networks and Intelligent Systems.

[14]  Mingyue Ding,et al.  Automatic needle segmentation in 3D ultrasound images using 3D improved Hough transform , 2008, SPIE Medical Imaging.

[15]  J. Duhamel,et al.  Parallel integral projection transform for straight electrode localization in 3-D ultrasound images , 2008, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[16]  R.V. Patel,et al.  Real-time parametric curved needle segmentation in 3D ultrasound images , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[17]  Christian Cachard,et al.  Multi-resolution parallel integral projection for fast localization of a straight electrode in 3D ultrasound images , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[18]  Christian Cachard,et al.  Line filtering for detection of microtools in 3D ultrasound data , 2009, 2009 IEEE International Ultrasonics Symposium.

[19]  Gabor Fichtinger,et al.  A new scheme for curved needle segmentation in three-dimensional ultrasound images , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[20]  Christian Cachard,et al.  Model Fitting Using RANSAC for Surgical Tool Localization in 3-D Ultrasound Images , 2010, IEEE Transactions on Biomedical Engineering.

[21]  Pingkun Yan,et al.  Automatic shape-based level set segmentation for needle tracking in 3-D TRUS-guided prostate brachytherapy. , 2012, Ultrasound in medicine & biology.

[22]  Christian Cachard,et al.  Tracking micro tool in a dynamic 3D ultrasound situation using Kalman filter and RANSAC algorithm , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

[23]  Allison M. Okamura,et al.  3D Segmentation of Curved Needles Using Doppler Ultrasound and Vibration , 2013, IPCAI.

[24]  David M. Mills,et al.  Automated catheter detection in volumetric ultrasound , 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

[25]  Maud Marchal,et al.  Real-time needle detection and tracking using a visually servoed 3D ultrasound probe , 2013, 2013 IEEE International Conference on Robotics and Automation.

[26]  A. Fenster,et al.  Needle segmentation using 3D Hough transform in 3D TRUS guided prostate transperineal therapy. , 2013, Medical physics.