Abstract: Topology optimization technique utilizes constant
element densities as design parameters. Finally, optimal distribution
contours of the material densities between voids (0) and solids (1) in
design domain represent the determination of topology. It means that
regions with element density values become occupied by solids in
design domain, while there are only void phases in regions where no
density values exist. Therefore the void regions of topology
optimization results provide design information to decide appropriate
depositions of web-opening in structure. Contrary to the basic
objective of the topology optimization technique which is to obtain
optimal topology of structures, this present study proposes a new idea
that topology optimization results can be also utilized for decision of
proper web-opening’s position. Numerical examples of linear
elastostatic structures demonstrate efficiency of methodological
design processes using topology optimization in order to determinate
the proper deposition of web-openings.
Abstract: In this study, we present an advanced detection
technique for mass type breast cancer based on texture information
of organs. The proposed method detects the cancer areas in three
stages. In the first stage, the midpoints of mass area are determined
based on AHE (Adaptive Histogram Equalization). In the second
stage, we set the threshold coefficient of homogeneity by using
MLE (Maximum Likelihood Estimation) to compute the uniformity
of texture. Finally, mass type cancer tissues are extracted from the
original image. As a result, it was observed that the proposed
method shows an improved detection performance on dense breast
tissues of Korean women compared with the existing methods. It is
expected that the proposed method may provide additional
diagnostic information for detection of mass-type breast cancer.