Scattering Operator and Spectral Clustering for Ultrasound Images: Application on Deep Venous Thrombi

Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators. Keywords—Deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering.

[1]  Guy Cloutier,et al.  Time-dependent hardening of blood clots quantitatively measured in vivo with shear-wave ultrasound imaging in a rabbit model of venous thrombosis. , 2014, Thrombosis research.

[2]  E. Oger,et al.  Venous thromboembolism (VTE) in Europe , 2007, Thrombosis and Haemostasis.

[3]  Sankaran Mahadevan,et al.  An improved method to construct basic probability assignment based on the confusion matrix for classification problem , 2016, Inf. Sci..

[4]  B. Solaiman,et al.  Comparative Neural Network Based Venous Thrombosis Echogenicity and Echostructure Characterization using Ultrasound Images , 2006, 2006 2nd International Conference on Information & Communication Technologies.

[5]  Simon K. Warfield,et al.  Spectral Clustering Algorithms for Ultrasound Image Segmentation , 2005, MICCAI.

[6]  G. Holland,et al.  Magnetic resonance venography for the detection of deep venous thrombosis: comparison with contrast venography and duplex Doppler ultrasonography. , 1993, Journal of vascular surgery.

[7]  Yan Pailhas,et al.  Texture recognition in synthetic aperture sonar images with scattering operators , 2011 .

[8]  D. Hamad,et al.  Introduction to spectral clustering , 2008, 2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications.

[9]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[10]  A. Mansour,et al.  Automatic clustering for MRI images, application on perfusion MRI of brain , 2016, 2016 2nd International Conference on Frontiers of Signal Processing (ICFSP).

[11]  R. Colman,et al.  Hemostasis and Thrombosis: Basic Principles and Clinical Practice , 1988 .

[12]  Hongbin Zha,et al.  Sorted Random Projections for robust texture classification , 2011, 2011 International Conference on Computer Vision.

[13]  Lewis D. Griffin,et al.  Texture classification with a dictionary of basic image features , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[15]  H. Ermert,et al.  Ultrasound elastography for the age determination of venous thrombi , 2005, Thrombosis and Haemostasis.

[16]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[17]  Huu-Giao Nguyen,et al.  Visual textures as realizations of multivariate log-Gaussian Cox processes , 2011, CVPR 2011.

[18]  Thibaud Berthomier,et al.  Deep venous thrombus characterization: ultrasonography, elastography and scattering operator , 2017 .

[19]  A. Mansour,et al.  Deep Venous Thrombosis: Database creation and image preprocessing , 2016, 2016 2nd International Conference on Frontiers of Signal Processing (ICFSP).

[20]  Stéphane Mallat,et al.  Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Stéphane Mallat,et al.  Deep roto-translation scattering for object classification , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Mario Fritz,et al.  THE KTH-TIPS database , 2004 .

[23]  Brian S. Garra,et al.  Elastography: history, principles, and technique comparison , 2015, Abdominal Imaging.

[24]  A. Mansour,et al.  Venous blood clot structure characterization using scattering operator , 2016, 2016 2nd International Conference on Frontiers of Signal Processing (ICFSP).

[25]  S. Mallat,et al.  Invariant Scattering Convolution Networks , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.