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Segmentation of liver in CT images is regarded as a challenge in image processing due to low-contrast of datasets, variety of liver shape, and its non-uniform texture; especially for abnormal cases. In this paper, we deal with normal and abnormal datasets as images containing two or more Gaussian components. We threshold a slice in a narrow band of each mode, find liver pixels based on a priori knowledge,...
A computational framework is presented for 3-D liver shape approximation and characterization in order to determine the accuracy of shape reconstruction via Spherical Harmonics expansion. Spherical Harmonics is a powerful mathematical tool for expanding the shape. But in medical domain, livers have very variation geometry, in shape, size, and volume. In this regards, we evaluated and optimized the...
The purpose of this study is to develop a new method for the registration of 3D cartilage plates in the MR data set. This technique traces local cartilage thickness changes over time. In a first rough registration step, the principal axes transformation (PAX) and landmark methods are used. In the second step, an improved iterative closest point (ICP) method is used. The point sets from segmentation...
Audio-to-video synchronization (AV-sync) may drift and is difficult to recover without dedicated human effort. In this work, we develop an interactive method to recover the drifted AV-sync by audiovisual correlation analysis. Given a video segment, a user specifies a rough time span during which a person is speaking. Our system first detects a speaker region using face detection. It then does a two-stage...
In this research, we propose a multi-step method for automatic segmentation of the hip femoral and acetabular cartilages from CT images. Differentiation of the acetabular and femoral cartilages in conventional CT images due to very narrow space and low intensity of the articular space is very difficult. For this reason, MRI of the hip under continuous leg traction is the choice for assessment of the...
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