UsimagTool : an Interactive Research Tool for Ultrasound Image Processing

We present here an open source software package called UsimagToolwhich consist of a set of algorithms and a graphic user interface (GUI) specially designed for research purposes in Ultrasound image processing. This tool is based on the C++ open source libraries ITK, VTK and FLTK. One of its main features is its modular and flexible architecture, which allow developers to modify or include image processing algorithms very fast. UsimagTool includes several algorithms developed specifically for Ultrasound data processing, that has been coded using the ITK and VTK convention. The algorithms included and described here are new implementations and they are not part of the official ITK or VTK releases. They are three filters (anisotropic Wiener, Speckle Reduction Anisotropic Diffusion, and Tensor guided Anisotropic Diff usion) one segmentation algorithm based on a Markov random field model, and a demons registration suitable for US data. There is also a user friendly GUI designed for segmentation and registration tasks, with three independent viewer s to display simultaneously three different data sets. The GU I can be easily adapted or modified with little effort for other tasks, for instance it can be redesigned for clinical use.

[1]  Osman Ratib,et al.  OsiriX: An Open-Source Software for Navigating in Multidimensional DICOM Images , 2004, Journal of Digital Imaging.

[2]  LeeJong-Sen.  Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980 .

[3]  Yasser M. Kadah,et al.  Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion , 2002, IEEE Transactions on Biomedical Engineering.

[4]  Sanjiv Sam Gambhir,et al.  AMIDE: a free software tool for multimodality medical image analysis. , 2003, Molecular imaging.

[5]  Jorge Herbert de Lira,et al.  Two-Dimensional Signal and Image Processing , 1989 .

[6]  Scott T. Acton,et al.  Speckle reducing anisotropic diffusion , 2002, IEEE Trans. Image Process..

[7]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[8]  P. Fillard,et al.  MEDINRIA : DT-MRI PROCESSING AND VISUALIZATION SOFTWARE , 2006 .

[9]  Santiago Aja-Fernández,et al.  On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering , 2006, IEEE Transactions on Image Processing.

[10]  K. Parker,et al.  Deviations from Rayleigh Statistics in Ultrasonic Speckle , 1988, Ultrasonic imaging.

[11]  Rachid Deriche,et al.  Fast algorithms for low-level vision , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[12]  Max A. Viergever,et al.  Efficient and reliable schemes for nonlinear diffusion filtering , 1998, IEEE Trans. Image Process..

[13]  Marco Nolden,et al.  The Medical Imaging Interaction Toolkit , 2005, Medical Image Anal..

[14]  E E de Lange,et al.  Renal volume measurements: accuracy and repeatability of US compared with that of MR imaging. , 1999, Radiology.

[15]  Andrew H. Gee,et al.  Decompression and speckle detection for ultrasound images using the homodyned k-distribution , 2003, Pattern Recognit. Lett..

[16]  W. Eric L. Grimson,et al.  An Integrated Visualization System for Surgical Planning and Guidance Using Image Fusion and Interventional Imaging , 1999, MICCAI.

[17]  Marcos Martín-Fernández,et al.  An approach for contour detection of human kidneys from ultrasound images using Markov random fields and active contours , 2005, Medical Image Anal..

[18]  X. Pennec,et al.  3D non-rigid registration by gradient descent on a Gaussian-windowed similarity measure using convolutions , 2000, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis. MMBIA-2000 (Cat. No.PR00737).

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

[20]  Douglas L. Jones,et al.  Line and boundary detection in speckle images , 1998, IEEE Trans. Image Process..

[21]  Jean-Philippe Thirion,et al.  Image matching as a diffusion process: an analogy with Maxwell's demons , 1998, Medical Image Anal..

[22]  Sridhar Lakshmanan,et al.  Simultaneous Parameter Estimation and Segmentation of Gibbs Random Fields Using Simulated Annealing , 1989, IEEE Trans. Pattern Anal. Mach. Intell..