A Novel Approach for Diagnosis of Breast Cancer using Ultrasound Imaging

Quader, Niamul

IUT Repository Home
→
Electrical and Electronics Engineering (EEE)
→
Thesis
→
Graduate
→
2012
→
View Item

dc.contributor.author	Quader, Niamul
dc.date.accessioned	2021-09-07T03:55:01Z
dc.date.available	2021-09-07T03:55:01Z
dc.date.issued	2012-11-15
dc.identifier.citation	[1] WHO (2012)Breast cancer: prevention and control. [2] WHO (2008). The global burden of disease: 2004 update. [3] Coleman MP et al. (2008). Cancer survival in five continents: a worldwide population-based study (CONCORD). Lancet Oncol, 9, 730–56. [4] Justo L. Sibala, MD; C. H. Joseph Chang, MD; Fritz Lin, MD; William R. Jewell, MD, Computed Tomographic MammographyDiagnosis of Mammographically and Clinically Occult Carcinoma of the Breast, Archives of Surgery . 1981;116(1):114-117. [5] Yip CH et al. (2008). Guideline implementation for breast healthcare in low- and middle-income countries: early detection resource allocation. Cancer, 113, 2244–56. [6] Vicini FA, Kestin L, Chen P, et al. Limited-field radiation therapy in the management of early-stage breast cancer, J National Cancer Insti tute 95, 1205-1210 (2003). [7] Halliwell, M. 2010 A tutorial on ultrasonic physics and imaging techniques. J.Eng. Med.: Proc. IMechE 224, 127–142. (doi:10.1243/09544119JEIM656). [8] Hasan Md. Kamrul, Anas Emran Mohammad Abu, Alam S. K., Lee Soo Yeol, Direct Mean Strain Estimation for Elastography Using Nearest-Neighbor Weighted Least-Squares Approach in the Frequency Domain, Ultrasound in Medicine and Biology, submitted, 2011. [9] Frederic L. Lizzi, Michael Astor, Tian Liu, Cheri Deng, D. Jackson Coleman, Ronald H. Silverman, Ultrasonic Spectrum Analysis for Tissue Assays and Therapy Evaluation, International Journal of Imaging Systems and Technology, Special Issue: Acoustical Tomography, Volume 8, Issue 1, pages 3–10, 1997. 45 [10] Alam S.K., Feleppa EJ, Rondeau M, Kalisz A, Garra BS, Ultrasonic Multi-Feature Analysis Procedure for Computer-Aided Diagnosis of Solid Breast Lesions, Ultrason Imaging. 2011 Jan;33(1):17-38. [11] American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) Atlas (American College of Radiology, Reston, VA, 2003). [12] Mandelson EB, Berg NA, Merritt CRB. Towards a standardized breast ultrasound lexicon bi-rads: ultrasound, Semin Roentgenol 36, 217-25 (2001). [13] Joo S, Yang YS, Moon WK, Kim HC. Computer-aided diagnosis of solid breast nodules: use of an artificial neural network based on multiple monographic features, IEEE Trans Med Imaging 23, 1292–1300 (2004). [14] http://www.scienceclarified.com/Ti-Vi/Tumor.html (2012). [15] American College of Radiology (ACR) Breast Imaging Reporting and Data System Atlas (BI-RADS Atlas). Reston, Va: © American College of Radiology; 2003. [16] Yao W, Zhao B, Zhao Y, Wang W, Qian G. Ultrasonographic texture analy sis of parenchymatous organs by the four-neighborhood-pixels algorithm, J Ultrasound Med 20, 465–471 (2001). [17] Chou Y-H, Tiu C-M, Hung G-S, et al. Stepwise logistic regression analysis of tumor contour features for breast ultra sound diagnosis, Ultrasound Med Biol 27, 1493–1498 (2001). [18] Hurst HE, Black RP, Simaika YM. Long Term Storage: An Experimental Study (Constable, London, 1965). [19] Feder J. Fractals (Plenum Press, New York, 1988). [20] Shankar PM, Dumane VA, Reid JM, et al. Classification of ultrasonic b-mode images of breast masses using nakagami distribution, IEEE Trans Ultrason Ferroelec Freq Contr 48, 569–580 (2001). 46 [21] Shankar PM, Dumane VA, Piccoli CW, et al. Computer-aided classification of breast masses in ultrasonic B-scans using a multiparameter approach, IEEE Trans Ultrason Ferroelec Freq Contr 50, 1002–1009 (2003). [22] Drukker K, Giger ML, Mendelson EB. Computerized analysis of shadowing on breast ultrasound for improved lesion detection. Med Phys 30, 1833–42 (2003). [23] Joo S, Yang YS, Moon WK, Kim HC. Computer-aided diagnosis of solid breast nodules: use of an artificial neural network based on multiple sonographic features, IEEE Trans Med Imag 23, 1292–1300 (2004). [24] Wahba G, Spline models for observational data, Philadelphia: Society for Industrial and Applied Mathematics, 1990. [25] Crochiere RE, Rabiner LR (1983). Multirate Digital Signal Processing. Englewood Cliffs, NJ: Prentice–Hall. [26] http://www.mathworks.com/help/techdoc (2012).	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/840
dc.description	Supervised by Dr. Kazi Khairul Islam Professor, Department of Electrical and Electronic Engineering Islamic University of Technology (IUT) Gazipur-1704, Bangladesh	en_US
dc.description.abstract	Breast cancer continues to be the most occurring cancer in women around the globe. With advancements in medical procedures, breast cancers are now virtually treatable in their early stage. Early detection, in turn, is vastly improved with community-wide organized sustainable programs. However, such schemes demand resources, and sizable amount of fund is being wasted for biopsy of benign lesions. Ultrasound imaging, because of its low ionization, effectiveness in diagnosing lesions of younger women and lesser resource intensiveness makes it a viable option for mass population programs. It has been shown to be effective in prevention of significant number of unnecessary biopsies. Thus, ultrasound imaging modality remains a prominent tool for diagnosis of breast cancer. Rigorous work is being done to improve overall imaging modality. In light of breast cancer, quantization of acoustic and morphometric features has proven to give good Receiver Operating Characteristic (ROC) area performance. However, ambiguity may still be there at concluding a lesion to be benign. The natural trend for such scenarios is the follow-up checkups recommended by experts. With thousands of follow-up checkups occurring each year, the need for a systematic study is imminent. We develop an effective algorithm that systematically processes over-time-data with the use of thin plate spline smoothing. This is followed by systematic categorization of different sets of physiological changes in light of benign and malignant lesions. Finally a versatile community wide scheme is outlined	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	A Novel Approach for Diagnosis of Breast Cancer using Ultrasound Imaging	en_US
dc.type	Thesis	en_US