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Manual segmentation of retinal blood vessels in optic fundus images is a tiresome task. Several methods have previously been proposed for the automatic segmentation of retinal blood vessels. In this paper we propose a classifier-based method. First the images are preprocessed so that the within class variability of the vessel and background classes are minimized. Next, the image is scanned with a...
The differential counting of white blood cells provides invaluable information to hematologist for diagnosis and treatment of many diseases. Manually counting of white blood cells is a tiresome, time-consuming and susceptible to error procedure. Due to the tedious nature of this process, an automatic system is preferable. In this automatic process, Segmentation of white blood cells is one of the most...
Biometrics is the technique of uniquely recognizing a person among a group of people. It is usually performed based on one or more of humanpsilas intrinsic physical or behavioral traits. One such trait is the electroencephalogram (EEG) signal. In this paper, the feasibility of visual evoked potential (VEP) in the gamma band of EEG signal, as a physiological trait, is studied, and used to identify...
Automatic recognition of white blood cells in hematological can be divided into four major parts: preprocessing, image segmentation, feature extraction and classification. Due to the multifarious nature of these cells and uncertainty in the hematological images, segmentation of white blood cells is one of the most important stages in this process. A scrupulous segmentation obviously reduces errors...
Many of diseases related to red blood cells can be diagnosed by analyzing the hematological images. The first step is to locate precisely the position of red blood cells. In this paper, a novel method based on polar transformation and run-length matrix is proposed for detecting red blood cells in hematological images. The multilayer perceptron was employed for classifying the feature vectors. This...
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