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Segmentation and analysis of histological images provides a valuable tool to gain insight into the biology and function of microglial cells in health and disease. Common image segmentation methods are not suitable for inhomogeneous histology image analysis and accurate classification of microglial activation states has remained a challenge. In this paper, we introduce an automated image analysis framework...
Vessel segmentation algorithms play a very important role in vascular disease diagnosis and prediction. Current vessel segmentation research uses mostly images of large vessels, which are relatively easy to extract, but segmenting microvasculature is more challenging and very important for analysing vascular disease such as Alzheimer's Diseases. The aim of this paper is to report experimental results...
This paper investigates the use of multifractal formalism for characterising 3D brain vasculature of 2 different mammalian species. Multifractal properties were found across all the 3D vascular models. Variations in the analysis results appear to correspond with vessel density ans morphology. The implication of the research is that multifractal analysis could potentially provide a useful tool for...
Object: to demonstrate the necessity of establishing chronic kidney disease registration system by the case of Guangdong provincial hospital of Chinese medicine. Method: laboratory test results of serum creatinine level and routine urinalysis of all in-hospital patients in year 2012 were collected through the hospital's information system. After excluding repeated test results, estimated glomerular...
Medical image registration is a difficult problem. Not only a registration algorithm needs to capture both large and small scale image deformations, it also has to deal with global and local image intensity variations. In this paper we describe a new multiresolution elastic image registration method that challenges these difficulties in image registration. To capture large and small scale image deformations,...
A novel method for classification of magnetic resonance brain images is presented in this paper. We construct a computational framework for discriminative image feature subspaces. Magnetic resonance images of patients in Alzheimer's disease and normal brain MR images are classified with support vector machines. The framework for the novel method bases on the extraction of gabor features from 2D-magnetic...
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