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Determination of breast tumors from B-Mode Ultrasound (US) image is a perplexing one. Researches employing statistical modeling such as Nakagami, Normal Inverse Gaussian (NIG) distributed parametric images in this classification task have already explored but experimentation of those statistical models on contourlet transformed coefficient image in breast tumor classification task has not reported yet. The proposed method is established by considering 250 clinical cases from a publicly available database. In this database each clinical case exists as *.bmp format. In the preprocessing step firstly, the ultrasound B-Mode image is binarized to detect the lesion contour. Then contourlet transformation is employed. These contourlet sub band coefficients are shown to be modeled effectively by Nakagami and NIG distributions. These Nakagami and NIG parametric images are obtained by estimating the parameters of those prior statistical distributions locally. Few shape and statistical features are chosen according to their effectiveness on those parametric images. The benign and malignant breast tumors are classified utilizing these features with different classifiers such as the support vector machine, k-nearest neighbors, fitted binary classification decision tree, binary Gaussian kernel classification model, linear classification models for binary learning with high-dimensional etc. It is observed that classification performance of NIG statistical model based parametric version of contourlet coefficient images gained better accuracy than those of Nakagami statistical model. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 7, Dec 2020 P 21-26

Numerical analysis is the area of mathematics that creates, analyzes, and implements algorithms for solving numerically the problems from real-world applications of algebra, geometry, and calculus, and they involve variables which vary continuously. Till now, numerous numerical methods have been introduced. Spectral method is one of those techniques used in applied mathematics and scientific computing to numerically solve certain differential equations, potentially involving the use of the Fast Fourier Transform (FFT). This study presents some of the fundamental ideas of spectral method. Orthogonal basis are used to establish computational algorithm. The accuracy and efficiency of proposed model are discussed. This manuscript estimates for the error between the exact and approximated discrete solutions. This paper shows that, grid points for polynomial spectral methods should lie approximately in a minimal energy configuration associated with inverse linear repulsion between points. The wave equation, linear and non-linear boundary value problems are solved using spectral method on the platform of MATLAB language. GANIT J. Bangladesh Math. Soc.Vol. 40 (2020) 28-42

Segmentation or lesion boundary detection in classification of Benign and Malignant breast tumors from B-Mode ultrasound image analysis is a challenging one. In this study, first a suitable frame is chosen by strain and velocity imaging from a raw radio frequency (RF) echo of clinical cases. The consequent B-Mode ultrasound (US) image is calculated and binarized. Finally, the lesion boundary is well-defined by binary dilation technique using MATLAB. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 5(1), Dec 2018 P 75-78