Real-Time Texture Analysis for Identifying Optimum Microbubble Concentration in 2-D Ultrasonic Particle Image Velocimetry

Ultrasound in Medicine and Biology

Volumn 37, Issue 8, 2011, Pages 1280-1291

  Niu, Lili ^a   Qian, Ming ^a   Yan, Liang ^b   Yu, Wentao ^a   Jiang, Bo ^a   Jin, Qiaofeng ^a   Wang, Yanping ^b   Shandas, Robin ^c   Liu, Xin ^a   Zheng, Hairong ^a,d  

^a SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^b MEDICAL COLLEGE OF JINAN UNIVERSITY   (China)

^c University of Colorado at Boulder   (United States)

^d INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Echo PIV; Flow imaging; Microbubbles; Texture analysis; Ultrasound contrast agents

Indexed keywords

ECHO PIV; FLOW IMAGING; MICROBUBBLES; TEXTURE ANALYSIS; ULTRASOUND CONTRAST AGENTS;

CONCENTRATION (PROCESS); FLOW VISUALIZATION; MAMMALS; ULTRASONICS; VELOCIMETERS; VELOCITY MEASUREMENT;

TEXTURES;

ECHO CONTRAST MEDIUM;

ACCURACY; ANIMAL EXPERIMENT; ARTICLE; B SCAN; CAROTID ARTERY FLOW; COMMON CAROTID ARTERY; CONCENTRATION RESPONSE; CONTRAST ENHANCEMENT; CONTROLLED STUDY; GRAY LEVEL CO OCCURRENCE MATRIX; IN VITRO STUDY; IN VIVO STUDY; K NEAREST NEIGHBOR CLASSIFIER; MICROBUBBLE; MOUSE; NONHUMAN; PARTICLE IMAGE VELOCIMETRY; PRIORITY JOURNAL; PULSATILE FLOW; STATISTICAL ANALYSIS; TWO DIMENSIONAL ULTRASONIC PARTICLE IMAGE VELOCIMETRY;

ANIMALS; BLOOD FLOW VELOCITY; CAROTID ARTERIES; CONTRAST MEDIA; MICE; MICROBUBBLES; PARTICLE SIZE; PHANTOMS, IMAGING; PULSATILE FLOW; RHEOLOGY; ULTRASONOGRAPHY;

EID: 79959859067     PISSN: 03015629     EISSN: 1879291X     Source Type: Journal    
DOI: 10.1016/j.ultrasmedbio.2011.05.006     Document Type: Article

References (39)

1. Al-Kadi O.S., Watson D. Texture analysis of aggressive and nonaggressive lung tumor CE CT images. IEEE Trans Biomed Eng 2008, 55:1822-1830.
2. Bader W., Bohmer S., Van Leeuwen P., Hackmann J., Westhof G., Hatzmann W. Does texture analysis improve breast ultrasound precision?. Ultrasound Obst Gyn 2002, 15:311-316.
3. Bouakaz A., De Jong N., Cachard C. Standard properties of ultrasound contrast agents. Ultrasound Med Biol 1998, 24:469-472.
4. Chabat F., Yang G.Z., Hansell D.M. Obstructive lung diseases: Texture classification for differentiation at CT. Radiology 2003, 228:871-877.
5. Chappard D., Chennebault A., Moreau M., Legrand E., Audran M., Basle M.F. Texture analysis of X-ray radiographs is a more reliable descriptor of bone loss than mineral content in a rat model of localized disuse induced by the clostridium botulinum toxin. Bone 2001, 28:72-79.
6. Chen D.W., Sengupta S.K., Welch R.M. Cloud field classification based upon high spatial resolution textural features: 2. simplified vector approaches. J Geophys Res 1989, 94:14749-14765.
7. Cheng A., Nguyen T.C., Malinowski M., Daughters G.T., Miller D.C., Ingels N.B. Heterogeneity of left ventricular wall thickening mechanisms. Circulation 2008, 118:713-721.
8. Cheng C., Tempel D., van Haperen R., van der Baan A., Grosveld F., Daemen M., Krams R., de Crom R. Atherosclerotic lesion size and vulnerability are determined by patterns of fluid shear stress. Circulation 2006, 113:2744-2753.
9. Christodoulou C.I., Pattichis C.S., Pantziaris M., Nicolaides A. Texture-based classification of atherosclerotic carotid plaques. IEEE Trans Med Imaging 2003, 22:902-912.
10. Clausi D.A. An analysis of co-occurrence texture statistics as a function of grey level quantization. Can J Remote Sensing 2002, 28:45-62.
11. Conners R., Trivedi M., Harlow C. Segmentation of a high-resolution urban scene using texture operators. Comput Vis Graph Image Process 1984, 25:273-310.
12. de Alejo R.P., Ruiz-Cabello J., Cortijo M., Rodriguez I., Echave I., Regadera J., Arrazola J., Aviles P., Barreiro P., Gargallo D., Grana M. Computer-assisted enhanced volumetric segmentation magnetic resonance imaging data using a mixture of artificial neural networks. Magn Reson Imaging 2003, 21:901-912.
13. Goldstein M. kn-nearest neighbor classification. IEEE Trans Inform Theory 1972, 18:627-630.
14. Haralick R.M., Shanmugam K., Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybemet 1973, 3:610-621.
15. Harrison L., Dastidar P., Eskola H., Jarvenpaa R., Pertovaara H., Luukkaala T., Kellokumpu-Lehtinen P.L., Soimakallio S. Texture analysis on MRI images of non-Hodgkin lymphoma. Comput Biol Med 2008, 38:519-524.
16. Herlidou S., Rolland Y., Bansard J.Y., Le Rumeur E., De Certaines J.D. Comparison of automated and visual texture analysis in MRI: Characterization of normal and diseased skeletal muscle. Magn Reson Imaging 1999, 17:1393-1397.
17. James D., Clymer B.D., Schmalbrock P. Texture detection of simulated microcalcification susceptibility effects in magnetic resonance imaging of breasts. J Magn Reson Imaging 2001, 13:876-881.
18. Jiang Y.N., Kohara K., Hiwada K. Association between risk factors for atherosclerosis and mechanical forces in carotid artery. Stroke 2000, 31:2319-2324.
19. Kim H.B., Hertzberg J.R., Lanning C., Shandas R. Noninvasive measurement of steady and pulsating velocity profiles and shear rates in arteries using echo PIV: In vitro validation studies. Ann Biomed Eng 2004, 32:1067-1076.
20. Kim H.B., Hertzberg J.R., Shandas R. Development and validation of echo PIV. Exp Fluids 2004, 36:455-462.
21. Kodym R., Seyss R. Darstellung der texturparameter von B-Mode-Sonogrammen in bildmassiger form. Ultraschall Med 1992, 13:116-118.
22. Kovalev V.A., Kruggel F., Gertz H.J., Von Cramon D.Y. Three-dimensional texture analysis of MRI brain datasets. IEEE Trans Med Imaging 2001, 20:424-433.
23. Lefebvre F., Meunier M., Thibault F., Laugier P., Berger G. Computerized ultrasound B-scan characterization of breast nodules. Ultrasound Med Biol 2000, 26:1421-1428.
24. Liu L.L., Zheng H.R., Williams L., Zhang F.X., Wang R., Hertzberg J.R., Shandas R. Development of a custom-designed echo particle image velocimetry system for multi-component hemodynamic measurements: System characterization and initial experimental results. Phys Med Biol 2008, 53:1397-1412.
25. Lv X.W., Bai C.G., Qiu G.B., Zhang S.F., Hu M.L. Relationship between texture features and mineralogy phases in iron ore sinter based on gray-level co-occurrence matrix. ISIJ Int 2009, 49:709-718.
26. McNitt-Gray M.F., Huang H.K., Sayre J.W. Feature selection in the pattern classification problem of digital chest radiograph segmentation. IEEE Trans Med Imaging 1995, 14:537-547.
27. Niu L.L., Qian M., Wan K., Yu W.T., Jin Q.F., Ling T., Gao S., Zheng H.R. Ultrasonic particle image velocimetry for improved flow gradient imaging: Algorithms, methodology and validation. Phys Med Biol 2010, 55:2103-2120.
28. Nystuen J.A., Garcia F.W. Sea ice classification using SAR backscatter statistics. IEEE Trans Geosci Remote Sensing 1992, 30:502-509.
29. Qian M., Niu L.L., Wang Y.P., Jiang B., Jin Q.F., Jiang C.X., Zheng H.R. Measurement of flow velocity fields in small vessel-mimic phantoms and vessels of small animals using micro ultrasonic particle image velocimetry (micro-EPIV). Phys Med Biol 2010, 55:6069-6088.
30. Shokr M.E. Evaluation of second-order texture parameters for sea ice classification from radar images. J Geophys Res 1991, 96:10625-10640.
31. Sivaramakrishna R., Powell K.A., Lieber M.L., Chilcote W.A., Shekhar R. Texture analysis of lesions in breast ultrasound images. Comput Med Imaging Graph 2002, 26:303-307.
32. Soh L.K., Tsatsoulis C. Texture analysis of SAR sea ice imagery using gray levelco-occurrence matrices. IEEE Trans Geosci Remote Sensing 1999, 37:780-795.
33. Sun Y., Kruse D.E., Dayton P.A., Ferrara K.W. High-frequency dynamics of ultrasound contrast agents. IEEE Trans Ultrason Ferrelectr Freq Control 2005, 52:1981-1991.
34. Tsui P.H., Liao Y.Y., Chang C.C., Kuo W.H., Chang K.J., Yeh C.K. Classification of benign and malignant breast tumors by 2-D analysis based on contour description and scatterer characterization. IEEE Trans Med Imaging 2010, 29:513-522.
35. Tsui P.H., Wang S.H. The effect of transducer characteristics on the estimation of Nakagami paramater as a function of scatterer concentration. Ultrasound Med Biol 2004, 30:1345-1353.
36. Wang Y., Itoh K., Taniguchi N., Toei H., Kawai F., Nakamura M., Omoto K., Yokota K., Ono T. Studies on tissue characterization by texture analysis with co-occurrence matrix method using ultrasonography and CT imaging. J Med Ultrason 2002, 29:211-223.
37. Zhang F.X., Lanning C., Mazzaro L., Barker A.J., Gates P.E., Strain W.D., Fulford J., Gosling O.E., Shore A.C., Bellenger N.G., Rech B., Chen J.S., Chen J., Shandas R. In vitro and preliminary in vivo validation of echo particle image velocimetry in carotid vascular imaging. Ultrasound Med Biol 2011, 37:450-464.
38. Zheng H.R., Liu L.L., Williams L., Hertzberg J.R., Lanning C., Shandas R. Real time multicomponent echo particle image velocimetry technique for opaque flow imaging. Appl Phys Lett 2006, 88:261915.
39. Zhong T., Tagare H.D., Beaty J.D. Evaluation of four probability distribution models for speckle in clinical cardiac ultrasound images. IEEE Trans Med Imaging 2006, 25:1483-1491.