Strain Estimation Techniques Using MATLAB Toolbox for Tissue Elasticity Imaging

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dc.contributor.author Ahmed, Sabbir
dc.contributor.author Bhuiyan, Tehjib Alim
dc.contributor.author Khan, Waliul Islam
dc.date.accessioned 2021-09-08T05:14:57Z
dc.date.available 2021-09-08T05:14:57Z
dc.date.issued 2013-11-15
dc.identifier.citation 1. Alam SK, Ophir J, Varghese T. Elastographic axial resolution criteria: an experimental study. IEEE Trans. Ultrason. Ferroel. Freq. Cont. 47(1): 304-309, 2000. 2. Alam SK, Lizzi FL, Varghese T, Felella EJ, Ramachandran S. Adaptive spectral strain estimators for elastography. Ultrasonic Imaging 26: 131-149, 2004. 3. Kenneth Leon Hoyt, Spectral Strain Estimation Techniques for Tissue Elasticity Imaging,2005. 4. Joel Edward Lindop.2D and 3D elasticity imaging using freehand ultrasound 2:38-40,2008. 5. M Halliwell.A tutorial on ultrasonic physics and imaging techniques,2009. 6. Frederic L. Lizzi,Michael Astor,Tian Liu,Cheri Deng,D. Jackson Coleman,Ronald H. Silverman. Ultrasonic Spectrum Analysis for Tissue Assays and Therapy Evaluation,1996. 7. George York and Yongmin Kim. Ultrasound Processing and Computing: Review and Future Directions,1999. 8. Graham Treece, Joel Lindop, Lujie Chen, James Housden, Richard Prager and Andrew Gee. Real-time quasi-static ultrasound elastography,2011. 9. Jeff Powers and Frederick Kremkau. Medical ultrasound systems,2011. en_US
dc.identifier.uri http://hdl.handle.net/123456789/868
dc.description Supervised by Prof. Dr. Kazi Khairul Islam, Department of Electrical and Electronic Engineering Islamic University of Technology A subsidiary organ of the Organization of Islamic Co-operation (OIC) Dhaka, Bangladesh en_US
dc.description.abstract Ultrasound is a widely used modality for both therapy and diagnosis in medicine and Biology. Currently, in the field of medical diagnosis, ultrasound is responsible for about one in five of all diagnostic images. This research project examines the applicability of strain estimation algorithms to improve the clinical value of tissue elasticity images. Pathological changes can be frequently correlated to changes in soft tissue stiffness. Despite the fact that many cancers often manifest themselves as stiff focal lesions, there location and shape can make them difficult, if not impossible, to detect during a palpation-based physical examination. The mechanical properties of tissue cannot be measured 7 | P a g e directly using any current imaging modality. However, an ultrasound-based technique known as elastography has evolved over the last fifteen years which is capable of estimating relative strain distributions in soft tissue. Under certain conditions, these strain images (elastograms) can give a clear depiction of the underlying tissue stiffness distributions, and thus, can be used as a clinical tool for the detection of pathological lesions. Conventionally elastographic techniques estimate tissue strain by tracking spatial features found in congruent pairs of ultrasonic echo backscattered signals before and after a small, quasistatic compression is applied to the tissue surface via the ultrasound transducer. Although this technique has shown promise from a clinical perspective in detecting both benign and malignant lesions of the breast and prostate, it is sensitive to extraneous motions that ultimately compromise the strain estimation procedure. To alleviate this problem, the applicability of strain estimation algorithms and techniques were examined. Both simulation and experimental (in vitro) results obtained using an elastographic phantom indicate that this approach holds promise to improve the clinical value of the images produced. Also, initial results obtained using a novel elastographic animal model further support the efficacy of spectral-based strain imaging in vivo. en_US
dc.language.iso en en_US
dc.publisher Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh en_US
dc.title Strain Estimation Techniques Using MATLAB Toolbox for Tissue Elasticity Imaging en_US
dc.type Thesis en_US


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