• Corpus ID: 9516919

Segmentation and Border Identification of Cells in Images of Peripheral Blood Smear Slides

@inproceedings{Ritter2007SegmentationAB,
  title={Segmentation and Border Identification of Cells in Images of Peripheral Blood Smear Slides},
  author={Nicola Ritter and James R. Cooper},
  booktitle={ACSC},
  year={2007}
}
We present an unsupervised blood cell segmentation algorithm for images taken from peripheral blood smear slides. Unlike prior algorithms the method is fast; fully automated; finds all objects---cells, cell groups and cell fragments---that do not intersect the image border; identifies the points interior to each object; finds an accurate one pixel wide border for each object; separates objects that just touch; and has been shown to work with a wide selection of red blood cell morphologies. The… 
Segmentation of RBC in Blood Smear Image using Discrete Shearlet Transform
TLDR
This paper attempts to develop a new technique to segment an RBC from blood smear images by extracting a color image from the light microscopic smear image and implementing discrete shearlet transform.
A Framework for White Blood Cell Segmentation in Microscopic Blood Images Using Digital Image Processing
TLDR
A proposed segmentation framework that consists of an integration of several digital image processing algorithms is able to extract the nucleus and cytoplasm region in a WBC image sample.
Detection of poor quality peripheral blood smear images used in detection of leukocytes and erythrocytes
TLDR
An automated method of detection of poor quality images is proposed thereby preventing them from wrongly analyzed, thus increasing the specificity and sensitivity of the system by almost 20 percentages.
Stained Blood Cell Detection and Clumped Cell Segmentation Useful for Malaria Parasite Diagnosis
TLDR
A new method for splitting clumped blood cells effectively into individual cells is presented and a complete framework for automating the detection of malaria parasites in Leishman-stained thin peripheral blood sample images is developed.
Segmentation of Peripheral Blood Smear Images Using Tissue-Like P Systems
TLDR
The proposed work aims at segmenting the nuclei of the White Blood Cells (WBCs) of the peripheral blood smear images, using tissue-like P Systems, which can help to identify various pathological conditions.
Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing
TLDR
A method based on K-means clustering and region growing is proposed in order to detect leukocytes from a blood smear microscopic image and segment its components, the nucleus and the cytoplasm.
Automated erythrocyte detection and classification from whole slide images
TLDR
A fully automated software targeted for erythrocyte detection and quantification from WSIs is developed and the potential employment of this software for the diagnosis of hematological disorders, such as sickle cell anemia is suggested.
An Image Processing Approach for Accurate Determination of Parasitemia in Peripheral Blood Smear Images
An interactive automatic procedure for detection of malaria from microscope blood images is presented. The user is required to select image from data set and the algorithm detects whether the blood
Red Blood Cell Cluster Separation From Digital Images for Use in Sickle Cell Disease
TLDR
This paper proposes a method for the analysis of the shape of erythrocytes in peripheral blood smear samples of sickle cell disease, which uses ellipse adjustments and a new algorithm for detecting notable points and applies a set of constraints that allow the elimination of significant image preprocessing steps proposed in previous studies.
Segmentation of Peripheral Blood Smear Images Using Tissue-Like P Systems
TLDR
The proposed work aims at segmenting the nuclei of the White Blood Cells (WBCs) of the peripheral blood smear images, which can help to identify various pathological conditions.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 39 REFERENCES
Analysis of infected blood cell images using morphological operators
TLDR
A morphological approach to cell image segmentation, that is, more accurate than the classical watershed-based algorithm, is introduced for detecting and classifying malaria parasites in images of Giemsa stained blood slides.
Segmentation of blood images using morphological operators
TLDR
Morphological approach to cell image segmentation more accurate than the classical watershed-based algorithm is introduced and a non-flat disk-shaped structuring element is used to enhance the roundness and compactness of the red cells improving the accuracy of the Classical watershed algorithm.
Image processing for automated erythrocyte classification.
TLDR
Digital image processing and pattern recognition techniques were applied to determine the feasibility of a natural n-space subgrouping of normal and abnormal peripheral blood erythrocytes into well separated categories, establishing subpopulations of red cells with quantifiable indices for the diagnosis of anemia, at the specimen level.
A Rapid Method for Counting Nucleated Erythrocytes on Stained Blood Smears by Digital Image Analysis
TLDR
A protocol for generating rapid counts of nucleated erythrocytes from digital micrographs of thin blood smears that can be used to estimate intensity of hematozoan infections in nonmammalian vertebrate hosts is described.
An Orientation‐Independent Imaging Technique for the Classification of Blood Cells
TLDR
An extension of this two-dimensional (2-D) method to a 3-D base is proposed and results of this technique using real-world image data of blood cell populations are given.
Clinical use of Automated Microscopes for Cell Analysis
In the survey paper on digital image processing in the United States, the author has provided a graph which indicates the exceptional recent growth in automated microscopy for white blood cell
Textural differences between AA and SS blood specimens as detected by image analysis.
TLDR
The ability of textural features to separate round cells into classes based on genotype suggests that high resolution image analysis may be an effective tool in the study and monitoring of sickle cell disease.
The observer error in peripheral blood cell classification.
  • J. Bacus
  • Medicine
    American journal of clinical pathology
  • 1973
An estimate of the observer classification error was obtained for six classes of peripheral blood leukocytes: lymphocytes, segmented and band neutrophils, eosinophils, basophils, and monocytes. The
Deformable Contour Method: A Constrained Optimization Approach
TLDR
A class of deformable contour methods using a constrained optimization approach of minimizing a contour energy function satisfying an interior homogeneity constraint is proposed and can be adapted to a broad range of medical images containing objects with vague, complex and/or irregular shape boundary.
The Use of an Image Analysing Computer for the Quantitation of Red Cell Morphological Characteristics
TLDR
Variances of cell area and colour density correlated subjectively with anisocytosis and anisochromasia, and histograms of these parameters demonstrated dual populations.
...
1
2
3
4
...