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Fluorescence microscopy image segmentation is a challenging task in fluorescence microscopy image analysis and high-throughput applications such as protein expression quantification and cell function investigation. In this paper, a novel local level set segmentation algorithm in a variational level set formulation via a correntropy-based k-means clustering (LLCK) is introduced for fluorescence microscopy...
Image processing and analysis is a useful tool for monitoring of activated sludge wastewater treatment plant. However its effectiveness is dependent on performance of the segmentation algorithms. The activated sludge plant is monitored by image processing and analysis of images acquired through trinocular microscope. The sample observed under microscope is collected from aeration tank of the plant...
In Vitro Fertilization (IVF) technology is used to help couple that have problem in their reproduction organs. However, the success rate of IVF is just 30%, so it is a challenging task to increase that success rate. In this paper, we proposed an ellipse detection method on single and multiple embryo image by modifying the ArcPSO method on ellipse fitting process and the process on extract the arc...
In order to accurately evaluate the microstructure parameters of Solid Oxide Fuel Cell (SOFC) electrode, this paper presents a novel image segmentation method based on Gaussian Mixture Model (GMM) to identify the three phases of electrode optical microscope image. Firstly, the spatial neighbor information is introduced into EM optimization algorithm to constrain the weighted probability distribution...
A combination of Gram-Schmidt method and cluster validation algorithm based Bayesian is proposed for nuclei segmentation on microscopic breast cancer image. Gram-Schmidt is applied to identify the cell nuclei on a microscopic breast cancer image and the cluster validation algorithm based Bayesian method is used for separating the touching nuclei. The microscopic image of the breast cancer cells are...
Image processing-based analysis of microscopic leukocyte helps in early detection of many diseases. It is a challenging issue to segment leukocytes under uneven imaging conditions since features of microscopic leukocyte images change in different labratories. This paper introduces an automatic robust method to segment leukocyte from blood microscopic images using intuitionistic fuzzy divergence based...
Segmentation of moving areas in high-speed biomedical video sequences captured by light microscope often contains some false-positive results which are generated by artifacts present in the image, e.g. air bubbles or red blood cells moving across the video. Such artifacts are common part of tissue samples under microscope. Moreover, if they closely interact with the objects of interest or they are...
We perform a short survey of image thresholding methods for very specific task, and assess their performance comparison. We analyse performance of adaptive thresholding methods concerning segmentation of immunonegative cells of follicular lymphoma tissue samples stained with 3,3′-Diaminobenzidine&Haematoxylin. We use artificial images based on experimental images that greatly simulates real samples...
In this paper, we propose an approach for achieving generalized segmentation of microorganisms in microscopy images. It employs a pixel-wise classification strategy based on local features. Multilayer perceptrons are utilized for classification of the local features and is trained for each specific segmentation problem using supervised learning. This approach was tested on five different segmentation...
Zooplankton is an important component in the water ecosystem and food chain. To understand the influence of zooplankton on the ecosystem a data collection is necessary. In research the automatic image based recognition of zooplankton is of growing interest. Several systems have been developed for zooplankton recognition on low resolution images. For large images approaches are seldom. Images of this...
In recent years, new optical microscopes have been developed, providing very high spatial resolution images called Whole Slide Images (WSI). The fast and accurate display of such images for visual analysis by pathologists and the conventional automated analysis remain challenging, mainly due to the image size (sometimes billions of pixels) and the need to analyze certain image features at high resolution...
Understanding cell movement is important in helping to prevent and cure damage and disease. Increasingly, this study is performed by obtaining video footage of cells in vitro. However, as the number of images obtained for cellular analysis increases, so does the need for automated segmentation of these images, since this is difficult and time consuming to perform manually. We propose to automate the...
In this contribution, an algorithm is presented, which is able to extract the shortest linear edge and the longest diagonal of each single isolated human insulin crystal region, which is found in an arbitrary image captured by an insitu microscope inside of a reactor, where a human insulin crystallization processes is taking place. First, the image regions of the single isolated crystals are segmented...
The goal of this paper is the reconstruction of topologically accurate 3-dimensional triangular meshes representing a complex, multi-layered plant tissue structure. Based on time sequences of meristem images of the model plant Arabidopsis thaliana, displaying fluorescence markers on either cell membranes or cell nuclei under confocal laser scanning microscopy, we aim at obtaining faithful reconstructions...
This work evaluates the possibility of measuring the biomass concentration and diagnosing the cell viability in non-stained cultures of yeast cells through image processing techniques. The algorithm presented in this study is validated on Saccharomyces cerevisiae cells. It processes the images acquired off-line on a bright field microscope, in order to enhance the features of the cells, to assess...
Malaria is caused by Plasmodium parasites that are able to invade human red blood cell. Many researches have focused on improving the accuracy of the diagnosis. Image processing method is able to increase results of malaria parasite cell detection. This paper is developed based on the image processing technique to detect three stages of Plasmodium parasites while in human host, i.e. trophozoite, schizont,...
Large number of diseases can be diagnosed by the counting and classification of blood cells. One type of the most common blood diseases is Acute Lymphoblastic Leukemia (ALL). Rapid and uncontrolled growth of immature leukemic cells (also named as blast cells) is used to characterize ALL. The morphological analysis of the bone marrow and blood smear is the primary step of diagnosis. Valuable information...
Urinary tract infection is one of the most common bacterial infection in humans and a major cause for outpatient consults. Spotting of pathogens in urine smears is taken to be the first clue that infection is present. In this paper, a new algorithm is proposed for color-feature extraction of microorganisms present in urine smear images. The proposed method was implemented on 60 test image samples...
In this paper, image segmentation process using thresholding technique is discussed. We focus our study for nuclei detection of Hematoxilin Eosin (HE) stained colon tissue for the cancer detection. Detection of cancer cell at early stage is very important and several studies are being carried out. In medical imaging for the processing of microscopic tissue images and especially the detection of cell...
In this study, we propose cell extraction method for solving the problem that previous research and common method cause extra segmentation and recognize single cell as plural cells. Proposed method consists of three steps. First, we separate the cell area from background of the image. Second, we classify the cell area into two groups by the size of area. Third, we extract cells from cell area classified...
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