The inverse problem involving the determination of a three-dimensional biological structure from images obtained by means of optical-sectioning microscopy is ill-posed. Regularization methods must often be used in order to obtain a reasonable solution. Recently, the Total Variation (TV) regularization, as proposed b y Rudin, Osher and Fatemi [ll], has become very popular for this purpose. A n i...

Pathological image analysis plays a significant role in effective disease diagnostics. In this article, a tool for diagnosis assistance by automatic segmentation of bone marrow images is introduced. The aim of our segmentation is to demarcate cell's component: nucleus, cytoplasm, red cells, and background. Different color spaces were used to extract color's features to profit of their complemen...

Accurate analysis of insect brain structures in digital confocal microscopic images is valuable and important to biology research needs. The first step is to segment meaningful structures from images. Active contour model, known as snakes, is widely used for segmentation of medical images. A new class of active contour model called gradient vector flow snake has been introduced in 1998 to overc...

The counting and analysis of blood cells allows the evaluation and diagnosis of a vast number of diseases. In particular, the analysis of white blood cells (WBCs) is a topic of great interest to hematologists. Nowadays the morphological analysis of blood cells is performed manually by skilled operators. This involves numerous drawbacks, such as slowness of the analysis and a nonstandard accurac...

We propose a new and efficient technique for incorporating contextual information into object classification. Most of the current techniques face the problem of exponential computation cost. In this paper, we propose a new general framework that incorporates partial context at a linear cost. This technique is applied to microscopic urinalysis image recognition, resulting in a significant improv...

In this paper, a new method is introduced for sperm detection in microscopic images for infertility treatment. In this method, firstly a hypothesis testing function is defined to separate sperms from plasma, non-sperm semen particles and noise. Then, some primary candidates are selected for sperms by watershed-based segmentation algorithm. Finally, candidates are either confirmed or rejected us...

In this paper we present a machine learning-based approach for detecting platelet cells in microscopic smear images. Counting how many platelets appeared in each smear image is one of the basic tasks done in many laboratories. In many cases this is still done by a human – laboratory technician. Due to very small size and often great quantity of those cells, precise estimating of the number of p...

Microscopic image enhancement is an important issue of image processing technique, which is used to improve the visual quality of image. This paper describes a novel multi resolution image segmentation algorithm for low DOF images. The algorithm is designed to separate a sharply focused object of interest from other foreground or background objects. The algorithm is fully automatic in that all ...

This paper explores the use of deformable mesh for registration of microscopic iris image sequences. The registration, as an effort for stabilizing and rectifying images corrupted by motion artifacts, is a crucial step toward leukocyte tracking and motion characterization for the study of immune systems. The image sequences are characterized by locally nonlinear deformations, where an accurate ...

when we can find a unique solution, a great deal of study has been done in this field and this is a hot research subject for to days study. So we could analyze the men's seaman and find out about fertility and infertility and from this find a true cure for this, since this will be a non invasive and low risk procedure, it will be greatly welcomed. In this research, the procedure has been based ...